Occupancy has significant impacts on building performance. However, in current building performance simulation programs, occupancy inputs are static and lack diversity, contributing to discrepancies between the simulated and actual building performance. This paper presents an Occupancy Simulator that simulates the stochastic behavior of occupant presence and movement in buildings, capturing the spatial and temporal occupancy diversity. Each occupant and each space in the building are explicitly simulated as an agent with their profiles of stochastic behaviors. The occupancy behaviors are represented with three types of models: (1) the status transition events (e.g., first arrival in office) simulated with Reinhart’s LIGHTSWITCH-2002 model, (2) the random moving events (e.g., from one office to another) simulated with Wang’s homogeneous Markov chain model, and (3) the meeting events simulated with a new stochastic model. A hierarchical data model was developed for the Occupancy Simulator, which reduces the amount of data input by using the concepts of occupant types and space types. Finally, a case study of a small office building is presented to demonstrate the use of the Simulator to generate detailed annual sub-hourly occupant schedules for individual spaces and the whole building. The Simulator is a web application freely available to the public and capable of performing a detailed stochastic simulation of occupant presence and movement in buildings. Future work includes enhancements in the meeting event model, consideration of personal absent days, verification and validation of the simulated occupancy results, and expansion for use with residential buildings.

In recent years, the application of district heating systems for the heat supply of residential districts has been increasing in Germany. Central supply systems can be very efficient due to diverse energy demand profiles which may lead to reduced installed equipment capacity. Load diversity in buildings has been investigated in former studies, especially for the electricity demand. However, little is known about the influence of single building characteristics (such as building envelope or hot water demand) on the overall heating peak load of a residential district. For measuring the diversity, the peak load ratio (PLR) index is used to represent the percentage reduction of peak load of a district system from a simple sum of individual peak loads of buildings. A total of 144 residential building load profiles have been created with the dynamic building simulation software IDA ICE for a theoretical analysis in which the PLR reaches 15%. Within this study, certain district features are identified which lead to higher diversity. Furthermore, these results are used in a district heating simulation model which confronts the possible advantage of reduced installed capacity with the practical disadvantage of heat distribution losses. Likewise, the influence of load density and the district´s building structure can be analyzed. This study shows that especially in districts with high load density, which consist of newly constructed buildings with low supply temperature and high influence of the hot water demand, the advantages of load diversity can be exploited.

Buildings in cities consume 30% to 70% of total primary energy, and improving building energy efficiency is one of the key strategies towards sustainable urbanization. Urban building energy models (UBEM) can support city managers to evaluate and prioritize energy conservation measures (ECMs) for investment and the design of incentive and rebate programs. This paper presents the retrofit analysis feature of City Building Energy Saver (CityBES) to automatically generate and simulate UBEM using EnergyPlus based on cities’ building datasets and user-selected ECMs. CityBES is a new open web-based tool to support city-scale building energy efficiency strategic plans and programs. The technical details of using CityBES for UBEM generation and simulation are introduced, including the workflow, key assumptions, and major databases. Also presented is a case study that analyzes the potential retrofit energy use and energy cost savings of five individual ECMs and two measure packages for 940 office and retail buildings in six city districts in northeast San Francisco, United States. The results show that: (1) all five measures together can save 23%-38% of site energy per building; (2) replacing lighting with light-emitting diode lamps and adding air economizers to existing heating, ventilation and air-conditioning (HVAC) systems are most cost-effective with an average payback of 2.0 and 4.3 years, respectively; and (3) it is not economical to upgrade HVAC systems or replace windows in San Franciso due to the city’s mild climate and minimal cooling and heating loads. The CityBES retrofit analysis feature does not require users to have deep knowledge of building systems or technologies for the generation and simulation of building energy models, which helps overcome major technical barriers for city managers and their consultants to adopt UBEM.

Weather has significant impacts on the thermal environment and energy use in buildings. Thus, accurate weather data are crucial for building performance evaluations. Traditionally, typical year data inputs are used to represent long-term weather data. However, there is no guarantee that a single year represents the changing climate well. In this study, the long-term representation of a typical year was assessed by comparing it to a 55-year actual weather data set. To investigate the weather impact on building energy use, 559 simulation runs of a prototype office building were performed for 10 large cities covering all climate zones in China. The analysis results demonstrated that the weather data varied significantly from year to year. Hence, a typical year cannot reflect the variation range of weather fluctuations. Typical year simulations overestimated or underestimated the energy use and peak load in many cases. With the increase in computational power of personal computers, it is feasible and essential to adopt multiyear simulations for full assessments of long-term building performance, as this will improve decision-making by allowing for the full consideration of variations in building energy use.

Ice-based thermal energy storage (TES) systems can shift peak cooling demand and reduce operational energy costs (with time-of-use rates) in commercial buildings. The accurate prediction of the cooling load, and the optimal control strategy for managing the charging and discharging of a TES system, are two critical elements to improving system performance and achieving energy cost savings. This study utilizes data-driven analytics and modeling to holistically understand the operation of an ice–based TES system in a shopping mall, calculating the system’s performance using actual measured data from installed meters and sensors. Results show that there is significant savings potential when the current operating strategy is improved by appropriately scheduling the operation of each piece of equipment of the TES system, as well as by determining the amount of charging and discharging for each day. A novel optimal control strategy, determined by an optimization algorithm of Sequential Quadratic Programming, was developed to minimize the TES system’s operating costs. Three heuristic strategies were also investigated for comparison with our proposed strategy, and the results demonstrate the superiority of our method to the heuristic strategies in terms of total energy cost savings. Specifically, the optimal strategy yields energy costs of up to 11.3% per day and 9.3% per month compared with current operational strategies. A one-day-ahead hourly load prediction was also developed using machine learning algorithms, which facilitates the adoption of the developed data analytics and optimization of the control strategy in a real TES system operation.

This paper describes a software system for automatically generating a reference (baseline) building energy model from the proposed (as-designed) building energy model. This system is built using the OpenStudio Software Development Kit (SDK) and is designed to operate on building energy models in the OpenStudio file format.

Small- and medium-sized commercial buildings owners and utility managers often look for opportunities for energy cost savings through energy efficiency and energy waste minimization. However, they currently lack easy access to low-cost tools that help interpret the massive amount of data needed to improve understanding of their energy use behaviors. Benchmarking is one of the techniques used in energy audits to identify which buildings are priorities for an energy analysis. Traditional energy performance indicators, such as the energy use intensity (annual energy per unit of floor area), consider only the total annual energy consumption, lacking consideration of the fluctuation of energy use behavior over time, which reveals the time of use information and represents distinct energy use behaviors during different time spans. To fill the gap, this study developed a general statistical method using 24-hour electric load shape benchmarking to compare a building or business/tenant space against peers. Specifically, the study developed new forms of benchmarking metrics and data analysis methods to infer the energy performance of a building based on its load shape. We first performed a data experiment with collected smart meter data using over 2,000 small- and medium-sized businesses in California. We then conducted a cluster analysis of the source data, and determined and interpreted the load shape features and parameters with peer group analysis. Finally, we implemented the load shape benchmarking feature in an open-access web-based toolkit (the Commercial Building Energy Saver) to provide straightforward and practical recommendations to users. The analysis techniques were generic and flexible for future datasets of other building types and in other utility territories.

This paper analyzes the performance of a novel two-pipe system that operates one water loop to simultaneously provide space heating and cooling with a water supply temperature of around 22 °C. To analyze the energy performance of the system, a simulation-based research was conducted. The two-pipe system was modelled using the equation-based Modelica modeling language in Dymola. A typical office building model was considered as the case study. Simulations were run for two construction sets of the building envelope and two conditions related to inter-zone air flows. To calculate energy savings, a conventional four-pipe system was modelled and used for comparison. The conventional system presented two separated water loops for heating and cooling with supply temperatures of 45 °C and 14 °C, respectively. Simulation results showed that the two-pipe system was able to use less energy than the four-pipe system thanks to three effects: useful heat transfer from warm to cold zones, higher free cooling potential and higher efficiency of the heat pump. In particular, the two-pipe system used approximately between 12% and 18% less total annual primary energy than the four-pipe system, depending on the simulation case considered.

To improve energy efficiency—during new buildings design or during a building retrofit—evaluating the energy savings potential of energy conservation measures (ECMs) is a critical task. In building retrofits, occupant behavior significantly impacts building energy use and is a leading factor in uncertainty when determining the effectiveness of retrofit ECMs. Current simulation-based assessment methods simplify the representation of occupant behavior by using a standard or representative set of static and homogeneous assumptions ignoring the dynamics, stochastics, and diversity of occupant's energy-related behavior in buildings. The simplification contributes to significant gaps between the simulated and measured actual energy performance of buildings.

This study presents a framework for quantifying the impact of occupant behaviors on ECM energy savings using building performance simulation. During the first step of the study, three occupant behavior styles (austerity, normal, and wasteful) were defined to represent different levels of energy consciousness of occupants regarding their interactions with building energy systems (HVAC, windows, lights and plug-in equipment). Next, a simulation workflow was introduced to determine a range of the ECM energy savings. Then, guidance was provided to interpret the range of ECM savings to support ECM decision making. Finally, a pilot study was performed in a real building to demonstrate the application of the framework. Simulation results show that the impact of occupant behaviors on ECM savings vary with the type of ECM. Occupant behavior minimally affects energy savings for ECMs that are technology-driven (the relative savings differ by less than 2%) and have little interaction with the occupants; for ECMs with strong occupant interaction, such as the use of zonal control variable refrigerant flow system and natural ventilation, energy savings are significantly affected by occupant behavior (the relative savings differ by up to 20%). The study framework provides a novel, holistic approach to assessing the uncertainty of ECM energy savings related to occupant behavior, enabling stakeholders to understand and assess the risk of adopting energy efficiency technologies for new and existing buildings.

The "human dimensions" of energy use in buildings refer to the energy-related behaviors of key stakeholders that affect energy use over the building life cycle. Stakeholders include building designers, operators, managers, engineers, occupants, industry, vendors, and policymakers, who directly or indirectly influence the acts of designing, constructing, living, operating, managing, and regulating the built environments, from individual building up to the urban scale. Among factors driving high-performance buildings, human dimensions play a role that is as significant as that of technological advances. However, this factor is not well understood, and, as a result, human dimensions are often ignored or simplified by stakeholders. This paper presents a review of the literature on human dimensions of building energy use to assess the state-of-the-art in this topic area. The paper highlights research needs for fully integrating human dimensions into the building design and operation processes with the goal of reducing energy use in buildings while enhancing occupant comfort and productivity. This research focuses on identifying key needs for each stakeholder involved in a building's lifecycle and takes an interdisciplinary focus that spans the fields of architecture and engineering design, sociology, data science, energy policy, codes, and standards to provide targeted insights. Greater understanding of the human dimensions of energy use has several potential benefits including reductions in operating cost for building owners;enhanced comfort conditions and productivity for building occupants;more effective building energy management and automation systems for building operators and energy managers; and the integration of more accurate control logic into the next generation of human-in-the-loop technologies. The review concludes by summarizing recommendations for policy makers and industry stakeholders for developing codes, standards, and technologies that can leverage the human dimensions of energy use to reliably predict and achieve energy use reductions in the residential and commercial buildings sectors.

Operational faults are common in the heating, ventilating, and air conditioning (HVAC) systems of existing buildings, leading to a decrease in energy efficiency and occupant comfort. Various fault detection and diagnostic methods have been developed to identify and analyze HVAC operational faults at the component or subsystem level. However, current methods lack a holistic approach to predicting the overall impacts of faults at the building level—an approach that adequately addresses the coupling between various operational components, the synchronized effect between simultaneous faults, and the dynamic nature of fault severity. This study introduces the novel development of a fault-modeling feature in EnergyPlus which fills in the knowledge gap left by previous studies. This paper presents the design and implementation of the new feature in EnergyPlus and discusses in detail the fault-modeling challenges faced. The new fault-modeling feature enables EnergyPlus to quantify the impacts of faults on building energy use and occupant comfort, thus supporting the decision making of timely fault corrections. Including actual building operational faults in energy models also improves the accuracy of the baseline model, which is critical in the measurement and verification of retrofit or commissioning projects. As an example, EnergyPlus version 8.6 was used to investigate the impacts of a number of typical operational faults in an office building across several U.S. climate zones. The results demonstrate that the faults have significant impacts on building energy performance as well as on occupant thermal comfort. Finally, the paper introduces future development plans for EnergyPlus fault-modeling capability.

District cooling systems are widely used in urban residential communities in China. Most district cooling systems are oversized;this leads to wasted investment and low operational efficiency and thus energy wastage. The accurate prediction of district cooling loads that supports rightsizing cooling plant equipment remains a challenge. This study developed a new stochastic modeling method that includes (1) six prototype house models representing a majority of apartments in the district, (2)occupant behavior models in residential buildings reflecting the temporal and spatial diversity and complexity based on a large-scale residential survey in China, and (3) a stochastic sampling process to represent all apartments and occupants in the district. The stochastic method was employed in a case study using the DeST simulation engine to simulate the cooling loads of a real residential district in Wuhan, China. The simulation results agree well with the actual measurement data based on five performance metrics representing the aggregated cooling loads, the peak cooling loads as well as the spatial load distribution,and the load profiles. Two currently used simulation methods were also employed to simulate the district cooling loads. The simulation results showed that oversimplified occupant behavior assumptions lead to significant overestimations of the peak cooling load and total district cooling loads. Future work will aim to simplify the workflow and data requirements of the stochastic method to enable its practical application as well as explore its application in predicting district heating loads and in commercial or mixed-use districts.

Occupant behavior (OB) in buildings is a leading factor influencing energy use in buildings. Quantifying this influence requires the integration of OB models with building performance simulation (BPS). This study reviews approaches to representing and implementing OB models in today’s popular BPS programs, and discusses weaknesses and strengths of these approaches and key issues in integrating of OB models with BPS programs. Two key findings are: (1) a common data model is needed to standardize the representation of OB models, enabling their flexibility and exchange among BPS programs and user applications; the data model can be implemented using a standard syntax (e.g., in the form of XML schema), and (2) a modular software implementation of OB models, such as functional mock-up units for co-simulation, adopting the common data model, has advantages in providing a robust and interoperable integration with multiple BPS programs. Such common OB model representation and implementation approaches help standardize the input structures of OB models, enable collaborative development of a shared library of OB models, and allow for rapid and widespread integration of OB models with BPS programs to improve the simulation of occupant behavior and quantification of their impact on building performance.

Occupancy is an important factor driving building performance. Static and homogeneous occupant schedules, commonly used in building performance simulation, contribute to issues such as performance gaps between simulated and measured energy use in buildings. Stochastic occupancy models have been recently developed and applied to better represent spatial and temporal diversity of occupants in buildings. However, there is very limited evaluation of the usability and accuracy of these models. This study used measured occupancy data from a real office building to evaluate the performance of an agent-based occupancy simulation model: the Occupancy Simulator. The occupancy patterns of various occupant types were first derived from the measured occupant schedule data using statistical analysis. Then the performance of the simulation model was evaluated and verified based on (1) whether the distribution of observed occupancy behavior patterns follows the theoretical ones included in the Occupancy Simulator, and (2) whether the simulator can reproduce a variety of occupancy patterns accurately. Results demonstrated the feasibility of applying the Occupancy Simulator to simulate a range of occupancy presence and movement behaviors for regular types of occupants in office buildings, and to generate stochastic occupant schedules at the room and individual occupant levels for building performance simulation. For future work, model validation is recommended, which includes collecting and using detailed interval occupancy data of all spaces in an office building to validate the simulated occupant schedules from the Occupancy Simulator.

As regional drought conditions continue deteriorating around the world, residential water use has been brought into the built environment spotlight. Nevertheless, the understanding of water use behavior in residential buildings is still limited. This paper presents data analytics and results from monitoring data of daily water use (DWU) in 50 single-family homes in Texas, USA. The results show the typical frequency distribution curve of the DWU per household and indicate personal income, education level and energy use of appliances all have statistically significant effects on the DWU per capita. Analysis of the water-intensive use demonstrates the residents tend to use more water in post-vacation days. These results help generate awareness of water use behavior in homes. Ultimately, this research could support policy makers to establish a water use baseline and inform water conservation programs.

In current building performance simulation programs, occupant presence and interactions with building systems are over-simplified and less indicative of real world scenarios, contributing to the discrepancies between simulated and actual energy use in buildings. Simulation results are normally presented using various types of charts. However, using those charts, it is difficult to visualize and communicate the importance of occupants’ behavior to building energy performance. This study introduced a new approach to simulating and visualizing energy-related occupant behavior in office buildings. First, the Occupancy Simulator was used to simulate the occupant presence and movement and generate occupant schedules for each space as well as for each occupant. Then an occupant behavior functional mockup unit (obFMU) was used to model occupant behavior and analyze their impact on building energy use through co-simulation with EnergyPlus. Finally, an agent-based model built upon AnyLogic was applied to visualize the simulation results of the occupant movement and interactions with building systems, as well as the related energy performance. A case study using a small office building in Miami, FL was presented to demonstrate the process and application of the Occupancy Simulator, the obFMU and EnergyPlus, and the AnyLogic module in simulation and visualization of energy-related occupant behaviors in office buildings. The presented approach provides a new detailed and visual way for policy makers, architects, engineers and building operators to better understand occupant energy behavior and their impact on energy use in buildings, which can improve the design and operation of low energy buildings.

Small commercial buildings in the United States consume 47 percent of all primary energy consumed in the building sector. Retrofitting small and medium commercial buildings may pose a steep challenge for owners, as many lack the expertise and resources to identify and evaluate cost-effective energy retrofit strategies. To address this problem, this project developed the Commercial Building Energy Saver (CBES), an energy retrofit analysis toolkit that calculates the energy use of a building, identifies and evaluates retrofit measures based on energy savings, energy cost savings, and payback. The CBES Toolkit includes a web app for end users and the CBES Application Programming Interface for integrating CBES with other energy software tools. The toolkit provides a rich feature set, including the following:

In a parallel effort the project team developed technologies to measure outdoor airflow rate; commercialization and use would avoid both excess energy use from over ventilation and poor indoor air quality resulting from under ventilation.

If CBES is adopted by California’s statewide small office and retail buildings, by 2030 the state can anticipate 1,587 gigawatt hours of electricity savings, 356 megawatts of non-coincident peak demand savings, 30.2 megatherms of natural gas savings, $227 million of energy-related cost savings, and reduction of emissions by 757,866 metric tons of carbon dioxide equivalent. In addition, consultant costs will be reduced in the retrofit analysis process.

CBES contributes to the energy savings retrofit field by enabling a straightforward and uncomplicated decision-making process for small and medium business owners and leveraging different levels of assessment to match user background, preference, and data availability.

Smart building management and control are adopted nowadays to achieve zero-net energy use in buildings. However, without considering the human dimension, technologies alone do not necessarily guarantee high performance in buildings. An office building was designed and built according to state-of-the-art design and energy management principles in 2008. Despite the expectations of high performance, the owner was facing high utility bills and low user comfort in the building located in Budapest, Hungary. The objective of the project was to evaluate the energy performance and comfort indices of the building, to identify the causes of malfunction and to elaborate a comprehensive energy concept. Firstly, current building conditions and operation parameters were evaluated. Our investigation found that the state-of-the-art building management system was in good conditions but it was operated by building operators and occupants who are not aware of the building management practice. The energy consumption patterns of the building were simulated with energy modelling software. The baseline model was calibrated to annual measured energy consumption, using actual occupant behaviour and presence, based on results of self-reported surveys, occupancy sensors and fan-coil usage data. Realistic occupant behaviour models can capture diversity of occupant behaviour and better represent the real energy use of the building. This way our findings and the effect of our proposed improvements could be more reliable. As part of our final comprehensive energy concept, we proposed intervention measures that would increase indoor thermal comfort and decrease energy consumption of the building. A parametric study was carried out to evaluate and quantify energy, comfort and return on investment of each measure. It was found that in the best case the building could save 23% of annual energy use. Future work includes the follow-up of: occupant reactions to intervention measures, the realized energy savings, the measurement of occupant satisfaction and behavioural changes.

Internal heat gains from occupants, lighting, and plug loads are significant components of the space cooling load in an office building. Internal heat gains vary with time and space. The spatial diversity is significant, even for spaces with the same function in the same building. The stochastic nature of internal heat gains makes determining the peak cooling load to size air-conditioning systems a challenge. The traditional conservative practice of considering the largest internal heat gain among spaces and applying safety factors overestimates the space cooling load, which leads to oversized air-conditioning equipment and chiller plants. In this study, a field investigation of several large office buildings in China led to the development of a new probabilistic approach that represents the spatial diversity of the design internal heat gain of each tenant as a probability distribution function. In a large office building, a central chiller plant serves all air handling units (AHUs), with each AHU serving one or more floors of the building. Therefore, the spatial diversity should be considered differently when the peak cooling loads to size the AHUs and chillers are calculated. The proposed approach considers two different levels of internal heat gains to calculate the peak cooling loads and size the AHUs and chillers in order to avoid oversizing, improve the overall operating efficiency, and thus reduce energy use.

This study introduces an interdisciplinary framework for investigating building-user interaction in office spaces. The framework is a synthesis of theories from building physics and social psychology including social cognitive theory, the theory of planned behavior, and the drivers-needs-actions-systems ontology for energy-related behaviors. The goal of the research framework is to investigate the effects of various behavioral adaptations and building controls (i.e., adjusting thermostats, operating windows, blinds and shades, and switching on/off artificial lights) to determine impacts on occupant comfort and energy-related operational costs in the office environment. This study attempts to expand state-of-the-art understanding of: (1) the environmental, personal, and behavioral drivers motivating occupants to interact with building control systems across four seasons, (2) how occupants’ intention to share controls is influenced by social-psychological variables such as attitudes, subjective norms, and perceived behavioral control in group negotiation dynamic, (3) the perceived ease of usage and knowledge of building technologies, and (4) perceived satisfaction and productivity. To ground the validation of the theoretical framework in diverse office settings and contexts at the international scale, an online survey was designed to collect cross-country responses from office occupants among 14 universities and research centers within the United States, Europe, China, and Australia.

Improving the sustainability of cities is crucial for meeting climate goals in the next several decades. One way this is being tackled is through innovation in district energy systems, which can take advantage of local resources and economies of scale to improve the performance of whole neighborhoods in ways infeasible for individual buildings. These systems vary in physical size, end use services, primary energy resources, and sophistication of control. They also vary enormously in their choice of optimization metrics while all under the umbrella-goal of improved sustainability.

This paper explores the implications of choice of metric on district energy systems using three case studies: Stanford University, the University of California at Merced, and the Richmond Bay campus of the University of California at Berkeley. They each have a centralized authority to implement large-scale projects quickly, while maintaining data records, which makes them relatively effective at achieving their respective goals. Comparing the systems using several common energy metrics reveals significant differences in relative system merit. Additionally, a novel bidirectional heating and cooling system is presented. This system is highly energy-efficient, and while more analysis is required, may be the basis of the next generation of district energy systems

With the increased urbanization in most countries worldwide, the urban heat island (UHI) effect, referring to the phenomenon that an urban area has higher ambient temperature than the surrounding rural area, has gained much attention in recent years. Given that Beijing is developing rapidly both in urban population and economically, the UHI effect can be significant. A long-term measured weather dataset from 1961 to 2014 for ten rural stations and seven urban stations in Beijing, was analyzed in this study, to understand the detailed temporal and spatial characteristics of the UHI in Beijing. The UHI effect in Beijing is significant, with an urban-to-rural temperature difference of up to 8℃ during the winter nighttime. Furthermore, the impacts of UHIs on building design and energy performance were also investigated. The UHI in Beijing led to an approximately 11% increase in cooling load and 16% decrease in heating load in the urban area compared with the rural area, whereas the urban heating peak load decreased 9% and the cooling peak load increased 7% because of the UHI effect. This study provides insights into the UHI in Beijing and recommendations to improve building design and decision-making while considering the urban microclimate.

Occupant behavior has significant impacts on building energy performance and occupant comfort. However, occupant behavior is not well understood and is often oversimplified in the building life cycle, due to its stochastic, diverse, complex, and interdisciplinary nature. The use of simplified methods or tools to quantify the impacts of occupant behavior in building performance simulations significantly contributes to performance gaps between simulated models and actual building energy consumption. Therefore, it is crucial to understand occupant behavior in a comprehensive way, integrating qualitative approaches and data- and model-driven quantitative approaches, and employing appropriate tools to guide the design and operation of low-energy residential and commercial buildings that integrate technological and human dimensions. This paper presents ten questions, highlighting some of the most important issues regarding concepts, applications, and methodologies in occupant behavior research. The proposed questions and answers aim to provide insights into occupant behavior for current and future researchers, designers, and policy makers, and most importantly, to inspire innovative research and applications to increase energy efficiency and reduce energy use in buildings.

China’s Design Standard for Energy Efficiency of Public Buildings (the Design Standard) is widely used in the design phase to regulate the energy efficiency of physical assets (envelope, lighting, HVAC) in buildings. However, the standard does not consider many important factors that influence the actual energy use in buildings, and this can lead to gaps between the design estimates and actual energy consumption. To achieve the national energy savings targets defined in the strategic 12th Five-Year Plan, China developed the first standard for energy consumption of buildings GB/T51161-2016 (the Consumption Standard). This study provides an overview of the Consumption Standard, identifies its strengths and weaknesses, and recommends future improvements. The analysis and discussion of the constraint value and the leading value, two key indicators of the energy use intensity, provide insight into the intent and effectiveness of the Consumption Standard. The results indicated that consistency between China’s Design Standard GB 50189-2015 and the Consumption Standard GB/T51161-2016 could be achieved if the Design Standard used the actual building operations and occupant behavior in calculating the energy use in Chinese buildings. The development of an outcome-based code in the U.S. was discussed in comparison with China’s Consumption Standard, and this revealed the strengths and challenges associated with implementing a new compliance method based on actual energy use in buildings in the U.S. Overall, this study provides important insights into the latest developments of actual consumption-based building energy standards, and this information should be valuable to building designers and energy policy makers in China and the U.S.

Traditionally, in building energy modeling (BEM) programs, occupancy inputs are deterministic and less indicative of real world scenarios, contributing todiscrepancies between simulated and actual energy use in buildings. This paper presents an agent-based occupancy simulator, which models each occupant asan agent with specified movement events and statistics of space uses. To reduce the amount of data inputs, the simulator allows users to group occupantswith similar behaviors as an occupant type, and spaces with similar function as a space type. It is a web-based application with friendly graphical userinterface, cloud computing, and data storage. A case study is presented to demonstrate the usage of the occupancy simulator and its integration withEnergyPlus and obFMU. It first shows the required data inputs and the results from the occupancy simulator. Then, the generated occupant schedules areused in the EnergyPlus and obFMU simulation to evaluate the impacts of occupant behavior on building energy performance. The simulation resultsindicate that the occupancy simulator can capture the diversity of space’s occupancy behavior rather than the static weekly profiles, and can generate realisticoccupancy schedules to support building performance simulation.

Variable air volume (VAV) systems and variable refrigerant flow (VRF) systems are popularly used in office buildings. This study investigated VAV and VRF systems in five typical office buildings in China, and compared their air conditioning energy use. Site survey and field measurements were conducted to collect data of building characteristics and operation. Measured cooling electricity use was collected from sub-metering in the five buildings. The sub-metering data, normalized by climate and operating hours, show that VRF systems consumed much less air conditioning energy by up to 70% than VAV systems. This is mainly due to the different operation modes of both system types leading to much fewer operating hours of the VRF systems. Building simulation was used to quantify the impact of operation modes of VRF and VAV systems on cooling loads using a prototype office building in China. Simulated results show the VRF operation mode leads to much less cooling loads than the VAV operation mode, by 42% in Hong Kong and 53% in Qingdao. The VRF systems operated in the part-time-part-space mode enabling occupants to turn on air-conditioning only when needed and when spaces were occupied, while the VAV systems operated in the full-time-full-space mode limiting occupants’ control of operation. The findings provide insights into VRF systems operation and controls as well as its energy performance, which can inform HVAC designers on system selection and building operators or facility managers on improving VRF system operations.

More than 80% of energy is consumed during operation phase of a building’s life cycle, so energy efficiency retrofit for existing buildings is considered a promising way to reduce energy use in buildings. The investment strategies of retrofit depend on the ability to quantify energy savings by “measurement and verification” (M&V), which compares actual energy consumption to how much energy would have been used without retrofit (called the “baseline” of energy use). Although numerous models exist for predicting baseline of energy use, a critical limitation is that occupancy has not been included as a variable. However, occupancy rate is essential for energy consumption and was emphasized by previous studies. This study develops a new baseline model which is built upon the Lawrence Berkeley National Laboratory (LBNL) model but includes the use of building occupancy data. The study also proposes metrics to quantify the accuracy of prediction and the impacts of variables. However, the results show that including occupancy data does not significantly improve the accuracy of the baseline model, especially for HVAC load. The reasons are discussed further. In addition, sensitivity analysis is conducted to show the influence of parameters in baseline models. The results from this study can help us understand the influence of occupancy on energy use, improve energy baseline prediction by including the occupancy factor, reduce risks of M&V and facilitate investment strategies of energy efficiency retrofit.

An increasing body of research is underlying the need to foster energy behaviors and interaction with technology as a way to achieve energy savings in office buildings. However, engaging office users into more “forgiving” comfort-adaptive behavior is not a trivial task, since neither consequences nor benefits for changing behavior have visible or tangible effects on them personally. Since the 70’s, survey studies in the field of building science have been used to gain better understanding of multidisciplinary drivers of occupant behavior with respect to comfort and energy requirements in buildings. Rather than focusing on individual behaviors – and influencing factors – purpose of this survey research is to provide quantitative descriptions on the collective and social motivations within the complexity of different social groups in working environment, under different geographical context, culture and norms. The resultant questionnaire survey emerges as a combination of traditional and adaptive comfort theories, merged with social science theory. The questionnaire explores to what extent the occupant energy-related behavior in working spaces is driven by a motivational sphere influenced by i) comfort requirements, ii) habits, iii) intentions and iv) actual control of building systems. The key elements of the proposed occupant behavior motivational framework are grounded on the Driver Need Action System framework for energy-related behaviors in buildings. Goal of the study is to construct an additional layer of standardized knowledge to enrich the state-of-the-art on energy-related behavior in office buildings.

HVAC operations play a significant role among variousdriving factors to improve energy performance ofbuildings. Extensive researches have been conducted onthe design efficiencies and control strategies of HVACsystem, but very few focused on the impacts of itsoperational faults on the building energy efficiency.Modeling and simulation of operational faults can leadto better understandings of the fault impacts and thussupport decision making of timely fault correctionswhich can further benefit the efficient system operation,improve the indoor thermal comfort, and prolong theequipment service life. Fault modeling is also critical toachieve more accurate and reliable model calibrations.This paper introduces the modeling and simulation ofoperational faults using EnergyPlus, a comprehensivewhole building performance simulation tool. The paperdiscusses the challenges of operational fault modeling,and compares three approaches to simulate operationalfaults using EnergyPlus. The paper also introduces thelatest development of native fault objects withinEnergyPlus. As an example, EnergyPlus version 8.4 isused to investigate the impacts of the integratedthermostat and humidistat faults in a typical officebuilding across several U.S. climate zones. The resultsdemonstrate that the faults create significant impacts onthe building energy performance as well as occupantthermal comfort. At last, the paper introduces the futuredevelopment plan of EnergyPlus for the furtherimprovement of its fault modeling capability.

Occupants are a critical impact factor of building energy consumption. Numerous previous studies emphasized the role of occupants and investigated the interactions between occupants and buildings. However, a fundamental problem, how to learn occupancy patterns and predict occupancy schedule, has not been well addressed due to highly stochastic activities of occupants and insufficient data. This study proposes a data mining based approach for occupancy schedule learning and prediction in office buildings. The proposed approach first recognizes the patterns of occupant presence by cluster analysis, then learns the schedule rules by decision tree, and finally predicts the occupancy schedules based on the inducted rules. A case study was conducted in an office building in Philadelphia, U.S. Based on one-year observed data, the validation results indicate that the proposed approach significantly improves the accuracy of occupancy schedule prediction. The proposed approach only requires simple input data (i.e., the time series data of occupant number entering and exiting a building), which is available in most office buildings. Therefore, this approach is practical to facilitate occupancy schedule prediction, building energy simulation and facility operation.

Occupant behavior in buildings is a leading factor influencing energy use in buildings. Low-cost behavioral solutions have demonstrated significant potential energy savings. Estimating the behavioral savings potential is important for a more effective design of behavior change interventions, which in turn will support more effective energy-efficiency policies. This study introduces a simulation approach to estimate the energy savings potential of occupant behavior measures. First it defines five typical occupant behavior measures in office buildings, then simulates and analyzes their individual and integrated impact on energy use in buildings. The energy performance of the five behavior measures was evaluated using EnergyPlus simulation for a real office building across four typical U.S. climates and two vintages. The Occupancy Simulator was used to simulate the occupant movement in each zone with inputs from the site survey of the case building. Based on the simulation results, the occupant behavior measures can achieve overall site energy savings as high as 22.9% for individual measures and up to 41.0% for integrated measures. Although energy savings of behavior measures would vary depending upon many factors, the presented simulation approach is robust and can be adopted for other studies aiming to quantify occupant behavior impact on building performance.

Small and medium-sized commercial buildings can be retrofitted to significantly reduce their energy use,however it is a huge challenge as owners usually lack of the expertise and resources to conduct detailedon-site energy audit to identify and evaluate cost-effective energy technologies. This study presents aDEEP (database of energy efficiency performance) that provides a direct resource for quick retrofitanalysis of commercial buildings. DEEP, compiled from the results of about ten million EnergyPlussimulations, enables an easy screening of ECMs (energy conservation measures) and retrofit analysis. Thesimulations utilize prototype models representative of small and mid-size offices and retails in Californiaclimates. In the formulation of DEEP, large scale EnergyPlus simulations were conducted on high performancecomputing clusters to evaluate hundreds of individual and packaged ECMs covering envelope,lighting, heating, ventilation, air-conditioning, plug-loads, and service hot water. The architecture andsimulation environment to create DEEP is flexible and can expand to cover additional building types,additional climates, and new ECMs. In this study DEEP is integrated into a web-based retrofit toolkit, theCommercial Building Energy Saver, which provides a platform for energy retrofit decision making byquerying DEEP and unearthing recommended ECMs, their estimated energy savings and financialpayback.

As rapid growth in the construction industry continues to occur in China, the increased demand for a higher standard living is driving significant growth in energy use and demand across the country. Building codes and standards have been implemented to head off this trend, tightening prescriptive requirements for fenestration component measures using methods similar to the US model energy code American Society of Heating, Refrigerating and Air-Conditioning Engineers (ASHRAE) 90.1. The objective of this study is to (a) provide an overview of applicable code requirements and current efforts within China to enable characterization and comparison of window and shading products, and (b) quantify the load reduction and energy savings potential of several key advanced window and shading systems, given the divergent views on how space conditioning requirements will be met in the future.

System-level heating and cooling loads and energy use performance were evaluated for a code-compliant large office building using the EnergyPlus building energy simulation program. Commercially-available, highly-insulating, low-emittance windows were found to produce 24-66% lower perimeter zone HVAC electricity use compared to the mandated energy-efficiency standard in force (GB 50189-2005) in cold climates like Beijing. Low-e windows with operable exterior shading produced up to 30-80% reductions in perimeter zone HVAC electricity use in Beijing and 18-38% reductions in Shanghai compared to the standard. The economic context of China is unique since the cost of labor and materials for the building industry is so low. Broad deployment of these commercially available technologies with the proper supporting infrastructure for design, specification, and verification in the field would enable significant reductions in energy use and greenhouse gas emissions in the near term.

Small commercial buildings in the United States consume 47% of the total primary energy of the buildings sector. Retrofitting small and medium commercial buildings poses a huge challenge for owners because they usually lack the expertise and resources to identify and evaluate cost-effective energy retrofit strategies. This paper presents the Commercial Building Energy Saver (CBES), an energy retrofit analysis toolkit, which calculates the energy use of a building, identifies and evaluates retrofit measures in terms of energy savings, energy cost savings and payback. The CBES Toolkit includes a web app (APP) for end users and the CBES Application Programming Interface (API) for integrating CBES with other energy software tools. The toolkit provides a rich set of features including: (1) Energy Benchmarking providing an Energy Star score, (2) Load Shape Analysis to identify potential building operation improvements, (3) Preliminary Retrofit Analysis which uses a custom developed pre-simulated database and, (4) Detailed Retrofit Analysis which utilizes real-time EnergyPlus simulations. CBES includes 100 configurable energy conservation measures (ECMs) that encompass IAQ, technical performance and cost data, for assessing 7 different prototype buildings in 16 climate zones in California and 6 vintages. A case study of a small office building demonstrates the use of the toolkit for retrofit analysis. The development of CBES provides a new contribution to the field by providing a straightforward and uncomplicated decision making process for small and medium business owners, leveraging different levels of assessment dependent upon user background, preference and data availability.

Lighting consumes about 20% to 40% of the total electricity use in large office buildings in China. Commonly in building simulations, static time schedules for typical weekdays, weekends and holidays are assumed to represent the dynamics of lighting energy use in buildings. This approach does not address the stochastic nature of lighting energy use, which can be influenced by occupant behavior in buildings. This study analyzes the main characteristics of lighting energy use over various timescales, based on the statistical analysis of measured lighting energy use data from 15 large office buildings in Beijing and Hong Kong. It was found that in these large office buildings, the 24-hourly variation in lighting energy use was mainly driven by the schedules of the building occupants. Outdoor illuminance levels had little impact on lighting energy use due to the lack of automatic daylighting controls (an effective retrofit measure to reduce lighting energy use) and the relatively small perimeter area exposed to natural daylight. A stochastic lighting energy use model for large office buildings was further developed to represent diverse occupant activities, at six different time periods throughout a day, and also the annual distribution of lighting power across these periods. The model was verified using measured lighting energy use from the 15 buildings. The developed stochastic lighting model can generate more accurate lighting schedules for use in building energy simulations, improving the simulation accuracy of lighting energy use in real buildings.

The space heating in residential buildings accounts for a considerable amount of the primary energy use. Therefore, understanding the operation and performance of space heating systems becomes crucial in improving occupant comfort while reducing energy use. This study investigated the behavior of occupants adjusting their thermostat settings and heating system operations in a 62-unit affordable housing complex in Revere, Massachusetts, USA. The data mining methods, including clustering approach and decision trees, were used to ascertain occupant behavior patterns. Data tabulating ON/OFF space heating states was assessed, to provide a better understanding of the intermittent operation of space heating systems in terms of system cycling frequency and the duration of each operation. The decision tree was used to verify the link between room temperature settings, house and heating system characteristics and the heating energy use. The results suggest that the majority of apartments show fairly constant room temperature profiles with limited variations during a day or between weekday and weekend. Data clustering results revealed six typical patterns of room temperature profiles during the heating season. Space heating systems cycled more frequently than anticipated due to a tight range of room thermostat settings and potentially oversized heating capacities. The results from this study affirm data mining techniques are an effective method to analyze large datasets and extract hidden patterns to inform design and improve operations.

Understanding the relationship between occupant behaviors and building energy consumption is one of the most effective ways to bridge the gap between predicted and actual energy consumption in buildings. However effective methodologies to remove the impact of other variables on building energy consumption and isolate the leverage of the human factor precisely are still poorly investigated. Moreover, the effectiveness of statistical and data mining approaches in finding meaningful correlations in data is largely undiscussed in literature. This study develops a framework combining statistical analysis with two data-mining techniques, cluster analysis and association rules mining, to identify valid window operational patterns in measured data. Analyses are performed on a data set with measured indoor and outdoor physical parameters and human interaction with operable windows in 16 offices. Logistic regression was first used to identify factors influencing window opening and closing behavior. Clustering procedures were employed to obtain distinct behavioral patterns, including motivational, opening duration, interactivity and window position patterns. Finally the clustered patterns constituted a base for association rules segmenting the window opening behaviors into two archetypal office user profiles for which different natural ventilation strategies as well as robust building design recommendations that may be appropriate. Moreover, discerned working user profiles represent more accurate input to building energy modeling programs, to investigate the impacts of typical window opening behavior scenarios on energy use, thermal comfort and productivity in office buildings

The paper presents a method and process to establish a database of energy efficiency performance (DEEP) to enable quick and accurate assessment of energy retrofit of commercial buildings. DEEP was compiled from results of about 35 million EnergyPlus simulations. DEEP provides energy savings for screening and evaluation of retrofit measures targeting the small and medium-sized office and retail buildings in California. The prototype building models are developed for a comprehensive assessment of building energy performance based on DOE commercial reference buildings and the California DEER prototype buildings. The prototype buildings represent seven building types across six vintages of constructions and 16 California climate zones. DEEP uses these prototypes to evaluate energy performance of about 100 energy conservation measures covering envelope, lighting, heating, ventilation, air-conditioning, plug-loads, and domestic hot water. DEEP consists the energy simulation results for individual retrofit measures as well as packages of measures to consider interactive effects between multiple measures. The large scale EnergyPlus simulations are being conducted on the super computers at the National Energy Research Scientific Computing Center of Lawrence Berkeley National Laboratory. The pre-simulation database is a part of an on-going project to develop a web-based retrofit toolkit for small and medium-sized commercial buildings in California, which provides real-time energy retrofit feedback by querying DEEP with recommended measures, estimated energy savings and financial payback period based on users’ decision criteria of maximizing energy savings, energy cost savings, carbon reduction, or payback of investment. The pre-simulated database and associated comprehensive measure analysis enhances the ability to performance assessments of retrofits to reduce energy use for small and medium buildings and business owners who typically do not have resources to conduct costly building energy audit. DEEP will be migrated into the DEnCity - DOE’s Energy City, which integrates large-scale energy data for multi-purpose, open, and dynamic database leveraging diverse source of existing simulation data.

This paper discusses design decisions for exportingModelica thermofluid flow components as FunctionalMockup Units. The purpose is to provide guidelinesthat will allow building energy simulation programsand HVAC equipment manufacturers to effectively useFMUs for modeling of HVAC components and systems.We provide an analysis for direct input-output dependenciesof such components and discuss how these dependenciescan lead to algebraic loops that are formedwhen connecting thermofluid flow components. Basedon this analysis, we provide recommendations that increasethe computing efficiency of such components andsystems that are formed by connecting multiple components.We explain what code optimizations are lost whenproviding thermofluid flow components as FMUs ratherthan Modelica code. We present an implementation ofa package for FMU export of such components, explainthe rationale for selecting the connector variables of theFMUs and finally provide computing benchmarks fordifferent design choices. It turns out that selecting temperaturerather than specific enthalpy as input and outputsignals does not lead to a measurable increase in computingtime, but selecting nine small FMUs rather than alarge FMU increases computing time by 70%

Variable refrigerant flow (VRF) systems vary the refrigerant flow to meet the dynamic zone thermalloads, leading to more efficient operations than other system types. This paper introduces a new modelthat simulates the energy performance of VRF systems in the heat pump (HP) operation mode. Com-pared with the current VRF-HP models implemented in EnergyPlus, the new VRF system model has morecomponent models based on physics and thus has significant innovations in: (1) enabling advanced con-trols, including variable evaporating and condensing temperatures in the indoor and outdoor units, andvariable fan speeds based on the temperature and zone load in the indoor units, (2) adding a detailedrefrigerant pipe heat loss calculation using refrigerant flow rate, operational conditions, pipe length, andpipe insulation materials, (3) improving accuracy of simulation especially in partial load conditions, and(4) improving the usability of the model by significantly reducing the number of user input performancecurves. The VRF-HP model is implemented in EnergyPlus and validated with measured data from fieldtests. Results show that the new VRF-HP model provides more accurate estimate of the VRF-HP systemperformance, which is key to determining code compliance credits as well as utilities incentive for VRFtechnologies.

Retrofit analysis toolkits can be used to optimize energy or cost savings from retrofit strategies, accelerating the adoption of ECMs (energy conservation measures) in buildings. This paper provides an up-todate review of the features and capabilities of 18 energy retrofit toolkits, including ECMs and the calculation engines. The fidelity of the calculation techniques, a driving component of retrofit toolkits, were evaluated. An evaluation of the issues that hinder effective retrofit analysis in terms of accessibility, usability, data requirement, and the application of efficiency measures, provides valuable insights into advancing the field forward. Following this review the general concepts were determined: (1) toolkits developed primarily in the private sector use empirically data-driven methods or benchmarking to provide ease of use, (2) almost all of the toolkits which used EnergyPlus or DOE-2 were freely accessible, but suffered from complexity, longer data input and simulation run time, (3) in general, there appeared to be a fine line between having too much detail resulting in a long analysis time or too little detail which sacrificed modeling fidelity. These insights provide an opportunity to enhance the design and development of existing and new retrofit toolkits in the future.

Most of the state-of-the-art building simulation programs implementmodels in imperative programming languages. This complicatesmodeling and excludes the use of certain efficient methods for simulationand optimization. In contrast, equation-based modeling languagesdeclare relations among variables, thereby allowing the use ofcomputer algebra to enable much simpler schematic modeling and togenerate efficient code for simulation and optimization.We contrast the two approaches in this paper. We explain howsuch manipulations support new use cases. In the first of two examples,we couple models of the electrical grid, multiple buildings,HVAC systems and controllers to test a controller that adjusts buildingroom temperatures and PV inverter reactive power to maintainpower quality. In the second example, we contrast the computingtime for solving an optimal control problem for a room-level modelpredictive controller with and without symbolic manipulations. Exploitingthe equation-based language led to 2, 200 times faster solution

When it comes to innovation in energy and building performance, one can expect leading-edge activity from the technology sector. As front-line innovators in design, materials science, and information management, developing and operating high-performance buildings is a natural extension of their core business.

The energy choices made by technology companies have broad importance given their influence on society at large as well as the extent of their own energy footprint. Microsoft, for example, has approximately 250 facilities around the world (30 million square feet of floor area), with significant aggregate energy use of approximately 4 million kilowatt-hours per day.

There is a degree of existing documentation of efforts to design, build, and operate facilities in the technology sector. However, the material is fragmented and typically looks only at a single company, or discrete projects within a company.Yet, there is no single resource for corporate planners and decision makers that takes stock of the opportunities and documents sector-specific case studies in a structured manner. This report seeks to fill that gap, doing so through a combination of generalized technology assessments (“Key Strategies”) and case studies (“Flagship Projects”).

Using portfolio analysis and individual detailed case studies, we studied the energy performance and drivers of energy use in 51 high-performance office buildings in the U.S., Europe, China, and other parts of Asia. Portfolio analyses revealed that actual site energy use intensity (EUI) of the study buildings varied by a factor of as much as 11, indicating significant variation in real energy use in HPBs worldwide. Nearly half of the buildings did not meet the American Society of Heating, Refrigerating, and Air Conditioning Engineers (ASHRAE) Standard 90.1-2004 energy target, raising questions about whether a building’s certification as high performing accurately indicates that a building is energy efficient and suggesting that improvement in the design and operation of HPBs is needed to realize their energy-saving potential. We studied the influence of climate, building size, and building technologies on building energy performance and found that although all are important, none are decisive factors in building energy use. EUIs were widely scattered in all climate zones. There was a trend toward low energy use in small buildings, but the correlation was not absolute; some small HPBs exhibited high energy use, and some large HPBs exhibited low energy use. We were unable to identify a set of efficient technologies that correlated directly to low EUIs. In two case studies, we investigated the influence of occupant behavior as well as operation and maintenance on energy performance and found that both play significant roles in realizing energy savings. We conclude that no single factor determines the actual energy performance of HPBs, and adding multiple efficient technologies does not necessarily improve building energy performance; therefore, an integrated design approach that takes account of climate, technology, occupant behavior, and operations and maintenance practices should be implemented to maximize energy savings in HPBs. These findings are intended to help architects, engineers, operators, and policy makers improve the design and operation of HPBs.

Building occupancy is a paramount factor in building energy simulations. Specifically, lighting, plug loads, HVAC equipment utilization, fresh air requirements and internal heat gain or loss greatly depends on the level of occupancy within a building. Developing the appropriate methodologies to describe and reproduce the intricate network responsible for human-building interactions are needed. Extrapolation of patterns from big data streams is a powerful analysis technique which will allow for a better understanding of energy usage in buildings. A three-step data mining framework is applied to discover occupancy patterns in office spaces. First, a data set of 16 offices with 10 minute interval occupancy data, over a two year period is mined through a decision tree model which predicts the occupancy presence. Then a rule induction algorithm is used to learn a pruned set of rules on the results from the decision tree model. Finally, a cluster analysis is employed in order to obtain consistent patterns of occupancy schedules. The identified occupancy rules and schedules are representative as four archetypal working profiles that can be used as input to current building energy modeling programs, such as EnergyPlus or IDA-ICE, to investigate impact of occupant presence on design, operation and energy use in office buildings.

Occupant behavior is now widely recognized as a major contributing factor to uncertainty of buildingperformance. While a surge of research on the topic has occurred over the past four decades, and particularlythe past few years, there are many gaps in knowledge and limitations to current methodologies.This paper outlines the state-of-the-art research, current obstacles and future needs and directions for thefollowing four-step iterative process: (1) occupant monitoring and data collection, (2) model development,(3) model evaluation, and (4) model implementation into building simulation tools. Major themesinclude the need for greater rigor in experimental methodologies; detailed, honest, and candid reportingof methods and results; and development of an efficient means to implement occupant behavior modelsand integrate them into building energy modeling programs.

Energy-related occupant behavior in buildings is difficult to define and quantify, yet critical to our understandingof total building energy consumption. Part I of this two-part paper introduced the DNAS(Drivers, Needs, Actions and Systems) framework, to standardize the description of energy-relatedoccupant behavior in buildings. Part II of this paper implements the DNAS framework into an XML(eXtensible Markup Language) schema, titled ‘occupant behavior XML’ (obXML). The obXML schema isused for the practical implementation of the DNAS framework into building simulation tools. The topologyof the DNAS framework implemented in the obXML schema has a main root element OccupantBehavior,linking three main elements representing Buildings, Occupants and Behaviors. Using theschema structure, the actions of turning on an air conditioner and closing blinds provide two examples ofhow the schema standardizes these actions using XML. The obXML schema has inherent flexibility torepresent numerous, diverse and complex types of occupant behaviors in buildings, and it can also beexpanded to encompass new types of behaviors. The implementation of the DNAS framework into theobXML schema will facilitate the development of occupant information modeling (OIM) by providinginteroperability between occupant behavior models and building energy modeling programs

Reducing energy consumption in the buildings sector requires significant changes, but technology alone may fail to guarantee efficient energy performance. Human behavior plays a pivotal role in building design, operation, management and retrofit, and is a crucial positive factor for improving the indoor environment, while reducing energy use at low cost. Over the past 40 years, a substantial body of literature has explored the impacts of human behavior on building technologies and operation. Often, need-action-event cognitive theoretical frameworks were used to represent human-machine interactions. In Part I of this paper a review of more than 130 published behavioral studies and frameworks was conducted. A large variety of data-driven behavioral models have been developed based on field monitoring of the human-building-system interaction. Studies have emerged scattered geographically around the world that lack in standardization and consistency, thus leading to difficulties when comparing one with another. To address this problem, an ontology to represent energy-related occupant behavior in buildings is presented. Accordingly, the technical DNAs framework is developed based on four key components: i) the Drivers of behavior, ii) the Needs of the occupants, iii) the Actions carried out by the occupants, and iv) the building systems acted upon by the occupants. This DNAs framework is envisioned to support the international research community to standardize a systematic representation of energy-related occupant behavior in buildings. Part II of this paper further develops the DNAs framework as an XML (eXtensible Markup Language) schema, obXML, for exchange of occupant information modeling and integration with building simulation tools.

Building model calibration is critical in bringing simulated energy use closer to the actual consumption. This paper presents a novel, automated model calibration approach that uses logic linking parameter tuning with bias pattern recognition to overcome some of the disadvantages associated with traditional calibration processes. The pattern-based process contains four key steps: (1) running the original precalibrated energy model to obtain monthly simulated electricity and gas use; (2) establishing a pattern bias, either Universal or Seasonal Bias, by comparing load shape patterns of simulated and actual monthly energy use; (3) using programmed logic to select which parameter to tune first based on bias pattern, weather and input parameter interactions; and (4) automatically tuning the calibration parameters and checking the progress using pattern-fit criteria. The automated calibration algorithm was implemented in the Commercial Building Energy Saver, a web-based building energy retrofit analysis toolkit. The proof of success of the methodology was demonstrated using a case study of an office building located in San Francisco. The case study inputs included the monthly electricity bill, monthly gas bill, original building model and weather data with outputs resulting in a calibrated model that more closely matched that of the actual building energy use profile. The novelty of the developed calibration methodology lies in linking parameter tuning with the underlying logic associated with bias pattern identification. Although there are some limitations to this approach, the pattern-based automated calibration methodology can be universally adopted as an alternative to manual or hierarchical calibration approaches.

Occupants are involved in a variety of activities in buildings, which drive them to move among rooms, enter or leave a building. In this study, occupancy is defined at four levels and varies with time: (1) the number of occupants in a building, (2) occupancy status of a space, (3) the number of occupants in a space, and (4) the space location of an occupant. Occupancy has a great influence on internal loads and ventilation requirement, thus building energy consumption. Based on a comprehensive review and comparison of literature on occupancy modeling, three representative occupancy models, corresponding to the levels 2, 3, and 4, are selected and implemented in a software module. Main contributions of our study include: (1) new methods to classify occupancy models, (2) the review and selection of various levels of occupancy models, and (3) new methods to integrate these model into a tool that can be used in different ways for different applications and by different audiences. The software can simulate more detailed occupancy in buildings to improve the simulation of energy use, and better evaluate building technologies in buildings. The occupancy of an office building is simulated as an example to demonstrate the use of the software module.

This paper presents an approach for speeding up Modelicamodels. Insight is provided into how Modelica modelsare solved and what determines the tool’s computationalspeed. Aspects such as algebraic loops, code efficiencyand integrator choice are discussed. This is illustratedusing simple building simulation examples andDymola. The generality of the work is in some casesverified using OpenModelica. Using this approach, amedium sized office building including building envelope,heating ventilation and air conditioning (HVAC)systems and control strategy can be simulated at a speedfive hundred times faster than real time.

The China Design Standard for Energy Efficiency in public buildings (GB 50189) debuted in 2005 when China completed the 10th Five-Year Plan. GB 50189-2005 played a crucial role in regulating the energy efficiency in Chinese commercial buildings. The standard was recently updated in 2014 to increase energy savings targets by 30% compared with the 2005 standard. This paper reviews the major changes to the standard, including expansion of energy efficiency coverage and more stringent efficiency requirements. The paper also discusses the interrelationship of the design standard with China's other building energy standards. Furthermore, comparisons are made with ASHRAE Standard 90.1-2013 to provide contrasting differences in efficiency requirements. Finally recommendations are provided to guide the future standard revision, focusing on three areas: (1) increasing efficiency requirements of building envelope and HVAC systems, (2) adding a whole-building performance compliance pathway and implementing a ruleset based automatic code baseline model generation in an effort to reduce the discrepancies of baseline models created by different tools and users, and (3) adding inspection and commissioning requirements to ensure building equipment and systems are installed correctly and operate as designed.

Buildings in the United States and China consumed 41% and 28% of the total primary energy in 2011, respectively. Good energy data are the cornerstone to understanding building energy performance and supporting research, design, operation, and policy making for low energy buildings. This paper presents initial outcomes from a joint research project under the U.S.-China Clean Energy Research Center for Building Energy Efficiency. The goal is to decode the driving forces behind the discrepancy of building energy use between the two countries; identify gaps and deficiencies of current building energy monitoring, data collection, and analysis; and create knowledge and tools to collect and analyze good building energy data to provide valuable and actionable information for key stakeholders. This paper first reviews and compares several popular existing building energy monitoring systems in both countries. Next a standard energy data model is presented. A detailed, measured building energy data comparison was conducted for a few office buildings in both countries. Finally issues of data collection, quality, sharing, and analysis methods are discussed. It was found that buildings in both countries performed very differently, had potential for deep energy retrofit, but that different efficiency measures should apply

Buildings consume more than one-third of the world’s primary energy. Reducing energy use in buildings with energy efficient technologies is feasible and also driven by energy policies such as energy benchmarking, disclosure, rating, and labeling in both the developed and developing countries. Current energy retrofits focus on the existing building stocks, especially older buildings, but the growing number of new high performance buildings built around the world raises a question that how these buildings perform and whether there are retrofit opportunities to further reduce their energy use. This is a new and unique problem for the building industry. Traditional energy audit or analysis methods are inadequate to look deep into the energy use of the high performance buildings. This study aims to tackle this problem with a new holistic approach powered by building performance data and analytics. First, three types of measured data are introduced, including the time series energy use, building systems operating conditions, and indoor and outdoor environmental parameters. An energy data model based on the ISO Standard 12655 is used to represent the energy use in buildings in a three-level hierarchy. Secondly, a suite of analytics were proposed to analyze energy use and to identify retrofit measures for high performance buildings. The data-driven analytics are based on monitored data at short time intervals, and cover three levels of analysis – energy profiling, benchmarking and diagnostics. Thirdly, the analytics were applied to a high performance building in California to analyze its energy use and identify retrofit opportunities, including: (1) analyzing patterns of major energy end-use categories at various time scales, (2) benchmarking the whole building total energy use as well as major end-uses against its peers, (3) benchmarking the power usage effectiveness for the data center, which is the largest electricity consumer in this building, and (4) diagnosing HVAC equipment using detailed time-series operating data. Finally, a few energy efficiency measures were identified for retrofit, and their energy savings were estimated to be 20% of the whole-building electricity consumption. Based on the analyses, the building manager took a few steps to improve the operation of fans, chillers, and data centers, which will lead to actual energy savings. This study demonstrated that there are energy retrofit opportunities for high performance buildings and detailed measured building performance data and analytics can help identify and estimate energy savings and to inform the decision making during the retrofit process. Challenges of data collection and analytics were also discussed to shape best practice of retrofitting high performance buildings.

This research developed new measurement and verification tools and new automated fault detection and diagnosis tools, and deployed them in the Universal Translator. The Universal Translator is a tool, developed by Pacific Gas and Electric, that manages large sets of measured data from building control systems and enables off‐line analysis of building performance. There were four technical projects following the program administration tasks identified as Project 1:

Project 2 addressed the need for less expensive measurement and verification tools to determine the costs and benefits of retrofits and retro‐commissioning at both the individual building level and the utility program level.

Project 4 combined previous work on duct leakage and fan modeling to develop a performance assessment method for existing fan/duct systems that could also be used in the analysis of retrofit measures identified by the tools in Projects 2 and 3 using the EnergyPlus simulation program to help select the most cost‐effective package of improvements.

Some of the diagnostic methods and tools developed in projects 2 through 4 were incorporated in the Universal Translator via a new application programming interface that was specified, developed and tested in Project 5. Combined, these tools support analyses of energy savings produced by new construction commissioning, retro‐commissioning, improved routine operations and code compliance. The new application programming interface could also facilitate future development, testing and deployment of new diagnostic tools.

This paper presents a new model to simulate energy performance of variable refrigerant flow (VRF) systems in heat pump operation mode (either cooling or heating is provided but not simultaneously). The main improvement of the new model is the introduction of the evaporating and condensing temperature in the indoor and outdoor unit capacity modifier functions. The independent variables in the capacity modifier functions of the existing VRF model in EnergyPlus are mainly room wet-bulb temperature and outdoor dry-bulb temperature in cooling mode and room dry-bulb temperature and outdoor wet-bulb temperature in heating mode. The new approach allows compliance with different specifications of each indoor unit so that the modeling accuracy is improved. The new VRF model was implemented in a custom version of EnergyPlus 7.2. This paper first describes the algorithm for the new VRF model, which is then used to simulate the energy performance of a VRF system in a Prototype House in California that complies with the requirements of Title 24 – the California Building Energy Efficiency Standards. The VRF system performance is then compared with three other types of HVAC systems: the Title 24-2005 Baseline system, the traditional High Efficiency system, and the EnergyStar Heat Pump system in three typical California climates: Sunnyvale, Pasadena and Fresno. Calculated energy savings from the VRF systems are significant. The HVAC site energy savings range from 51 to 85%, while the TDV (Time Dependent Valuation) energy savings range from 31 to 66% compared to the Title 24 Baseline Systems across the three climates. The largest energy savings are in Fresno climate followed by Sunnyvale and Pasadena. The paper discusses various characteristics of the VRF systems contributing to the energy savings. It should be noted that these savings are calculated using the Title 24 prototype House D under standard operating conditions. Actual performance of the VRF systems for real houses under real operating conditions will vary.

Energy consumed by buildings accounts for one third of the world’s total primary energy use. Associated with the conscious of energy savings in buildings, High Performance Buildings (HPBs) has surged across the world, with wide promotion and adoption of various performance rating and certification systems. It is valuable to look into the actual energy performance of HPBs and to understand their influencing factors.To shed some light on this topic, this paper conducted a series of portfolio analysis based on a database of 51 high performance office buildings across the world. Analyses showed that the actual site Energy Use Intensity (EUI) of the 51 buildings varied by a factor of up to 11, indicating a large scale of variation of the actual energy performance of the current HPBs. Further analysis of the correlation between EUI and climate elucidated ubiquitous phenomenon of EUI scatter throughout all climate zones, implying that the weather is not a decisive factor, although important, for the actual energy consumption of an individual building. On the building size via EUI, analysis disclosed that smaller buildings have a tendency to achieving lower energy use. Even so, the correlation is not absolute since some large buildings demonstrated low energy use while some small buildings performed opposite. Concerning the technologies, statistics indicated that the application of some technologies had correlations with some specific building size and climate characteristic. However, it was still hard to pinpoint a set of technologies which was directly correlative with a group of low EUI buildings.It is concluded that no a single factor essentially determines the actual energy performance of HPBs. To deliver energy-efficient buildings, an integrated design taking account of climate, technology, occupant behavior as well as operation and maintenance should be implemented.

Overtime is a common phenomenon around the world. Overtime drives both internal heat gains from occupants, lighting and plug-loads, and HVAC operation during overtime periods. Overtime leads to longer occupancy hours and extended operation of building services systems beyond normal working hours, thus overtime impacts total building energy use. Current literature lacks methods to model overtime occupancy because overtime is stochastic in nature and varies by individual occupants and by time. To address this gap in the literature, this study aims to develop a new stochastic model based on the statistical analysis of measured overtime occupancy data from an office building. A binomial distribution is used to represent the total number of occupants working overtime, while an exponential distribution is used to represent the duration of overtime periods. The overtime model is used to generate overtime occupancy schedules as an input to the energy model of a second office building. The measured and simulated cooling energy use during the overtime period is compared in order to validate the overtime model. A hybrid approach to energy model calibration is proposed and tested, which combines ASHRAE Guideline 14 for the calibration of the energy model during normal working hours, and a proposed KS test for the calibration of the energy model during overtime. The developed stochastic overtime model and the hybrid calibration approach can be used in building energy simulations to improve the accuracy of results, and better understand the characteristics of overtime in office buildings.Keywords:

Building energy simulation programs are effective tools for the evaluation of building energy saving and optimization of design. The fact that large discrepancies exist in simulated results when different BEMPs are used to model the same building has caused wide concern. Urgent research is needed to identify the main elements that contribute towards the simulation results. This technical report summarizes methodologies, processes, and the main assumptions of three building energy modeling programs (BEMPs) for HVAC calculations: EnergyPlus, DeST, and DOE-2.1E, and test cases are designed to analyze the calculation process in detail. This will help users to get a better understanding of BEMPs and the research methodology of building simulation. This will also help build a foundation for building energy code development and energy labeling programs.

U.S. and China are the world’s top two economics. Together they consumed one-thirdof the world’s primary energy. It is an unprecedented opportunity and challenge forgovernments, researchers and industries in both countries to join together to addressenergy issues and global climate change. Such joint collaboration has huge potential increating new jobs in energy technologies and services.Buildings in the US and China consumed about 40% and 25% of the primary energy inboth countries in 2010 respectively. Worldwide, the building sector is the largestcontributor to the greenhouse gas emission. Better understanding and improving theenergy performance of buildings is a critical step towards sustainable developmentand mitigation of global climate change.This project aimed to develop a standard methodology for building energy datadefinition, collection, presentation, and analysis; apply the developed methods to astandardized energy monitoring platform, including hardware and software, to collectand analyze building energy use data; and compile offline statistical data and onlinereal-time data in both countries for fully understanding the current status of buildingenergy use. This helps decode the driving forces behind the discrepancy of buildingenergy use between the two countries; identify gaps and deficiencies of currentbuilding energy monitoring, data collection, and analysis; and create knowledge andtools to collect and analyze good building energy data to provide valuable andactionable information for key stakeholders.Key research findings were summarized as follows:1. Identified the need for a standard data model and platform to collect, process,analyze, and exchange building performance data due to different definitionsof energy use and boundary, difficulty in exchanging data, and lack of currentstandards.2. Compared energy monitoring systems to identify gaps, including iSagy, PulseEnergy, SkySpark, sMap, EPP, ION, and Metasys.3. Contributed to develop a standard data model to represent energy use inbuildings (ISO standard 12655 and a Chinese national standard)4. Determined that buildings in the United States and China are very different indesign, operation, maintenance, occupant behavior: U.S. buildings have morestringent comfort standards regarding temperature, ventilation, lighting, andhot-water use and therefore higher internal loads and operating hours, andChina buildings having higher lighting energy use, seasonal HVAC operation,more operators, more use of natural ventilation, less outdoor ventilation air,and wider range of comfort temperature.5. Completed data collection for six office buildings, one in UC Merced campus,one in Sacramento, one in Berkeley, one in George Tech campus, and two inBeijing.6. Compiled a source book of 10 selected buildings in the United States and Chinawith detailed descriptions of the buildings, data points, and monitoringsystems, and containing energy analysis of each building and an energybenchmarking among all buildings.7. Recognized limited availability of quality data, particularly with long periods oftime-interval data, and general lack of value for good data and large datasets.8. Compiled a building energy database, with detailed energy end use at 1-houror 15-minute time interval, of six office buildings – four in the U.S. and two inChina. The database is available to the public and is a valuable resource forbuilding research.9. Developed methods and used them in data analysis of building performancefor the five buildings with adequate data, including energy benchmarking,profiling (daily, weekly, monthly), and diagnostics.10. Recommended energy efficiency measures for building retrofit in bothcountries. U.S. buildings show more potential savings by reducing operationtime, reducing plug-loads, expanding comfort temperature range, and turningoff lights or equipment when not in use; while Chinese buildings can saveenergy by increasing lighting system efficiency, and improving envelopeinsulation and HVAC equipment efficiency.The research outputs from the project can help better understand energyperformance of buildings, improve building operations to reduce energy wasteand increase efficiency, identify retrofit opportunities for existing buildings, andprovide guideline to improve the design of new buildings. The standardizedenergy monitoring and analysis platform as well as the collected real building datacan also be used for other CERC projects that need building energy measurements,and be further linked to building energy benchmarking and rating/labelingsystems.

This paper describes how to use the recently implemented Functional Mock-up Unit (FMU) for co-simulation import interface in EnergyPlus to link EnergyPlus with simulation tools packaged as FMUs. The interface complies with the Functional Mock-up Interface (FMI) for co-simulation standard version 1.0, which is an open standard designed to enable links between different simulation tools that are packaged as FMUs. This article starts with an introduction of the FMI and FMU concepts. We then discuss the implementation of the FMU import interface in EnergyPlus. After that, we present two use cases. The first use case is to model a HVAC system in Modelica, export it as an FMU, and link it to a room model in EnergyPlus. The second use case is an extension of the first case where a shading controller is modeled in Modelica, exported as an FMU, and used in the EnergyPlus room model to control the shading device of one of its windows. In both cases, the FMUs are imported into EnergyPlus which models the building envelope and manages the data-exchange between the envelope and the systems in the FMUs during run-time.

Occupancy profile is one of the driving factors behind discrepancies between the measured and simulated energy consumption of buildings. The frequencies of occupants leaving their offices and the corresponding durations of absences have significant impact on energy use and the operational controls of buildings. This study used statistical methods to analyze the occupancy status, based on measured lighting-switch data in five-minute intervals, for a total of 200 open-plan (cubicle) offices. Five typical occupancy patterns were identified based on the average daily 24-hour profiles of the presence of occupants in their cubicles. These statistical patterns were represented by a one-square curve, a one-valley curve, a two-valley curve, a variable curve, and a flat curve. The key parameters that define the occupancy model are the average occupancy profile together with probability distributions of absence duration, and the number of times an occupant is absent from the cubicle. The statistical results also reveal that the number of absence occurrences decreases as total daily presence hours decrease, and the duration of absence from the cubicle decreases as the frequency of absence increases. The developed occupancy model captures the stochastic nature of occupants moving in and out of cubicles, and can be used to generate a more realistic occupancy schedule. This is crucial for improving the evaluation of the energy saving potential of occupancy based technologies and controls using building simulations. Finally, to demonstrate the use of the occupancy model, weekday occupant schedules were generated and discussed.

Natural ventilation, used appropriately, has the potential to provide both significant HVAC energy savings, and improvements in occupant satisfaction.

Central to the development of natural ventilation models is the need to accurately represent the behavior of building occupants. The work covered in this paper describes a method of implementing a stochastic window model in EnergyPlus. Simulated window use data from three stochastic window opening models was then compared to measured window opening behavior, collected in a naturally-ventilated office in California. Recommendations regarding the selection of stochastic window use models, and their implementation in EnergyPlus, are presented.

A design tool to evaluate the heat and mass transfer effectiveness and pressure drop of a membrane-based enthalpy exchanger was developed and then used to optimize the configuration of an enthalpy exchanger for minimum pressure drop and maximum heat recovery effectiveness. Simulation was used in a parametric study to investigate the energy saving potential of the enthalpy recovery system. The case without energy recovery and air side economizer was used as a baseline. Two comparison cases for the implementation of enthalpy recovery with and without air side economizer were simulated in EnergyPlus. A case using a desiccant wheel for energy recovery was also investigated for comparison purposes. The simulation results show significant energy saving benefits from applying a low pressure drop, high effectiveness enthalpy exchanger in two US cities representing a range of humid climates. The sensitivity of the energy savings potential to pressure drop and heat and mass transfer effectivenesses is also presented.

Most commercial buildings do not perform as well in practice as intended by the design and their performances often deteriorate over time. Reasons include faulty construction, malfunctioning equipment, incorrectly configured control systems and inappropriate operating procedures. One approach to addressing this problems is to compare the predictions of an energy simulation model of the building to the measured performance and analyze significant differences to infer the presence and location of faults. This paper presents a framework that allows a comparison of building actual performance and expected performance in real time. The realization of the framework utilized the EnergyPlus, the Building Controls Virtual Test Bed (BCVTB) and the Energy Management and Control System (EMCS) was developed. An EnergyPlus model that represents expected performance of a building runs in real time and reports the predicted building performance at each time step. The BCVTB is used as the software platform to acquire relevant inputs from the EMCS through a BACnet interface and send them to the EnergyPlus and to a database for archiving. A proof-of-concept demonstration is also presented.

The accurate prediction of cooling and dehumidification coil performance is important in model-based fault detection and in the prediction of HVAC system energy consumption for support of both design and operations. It is frequently desirable to use a simple cooling coil model that does not require detailed specification of coil geometry and material properties. The approach adopted is to match the overall UA of the coil to the rating conditions and to estimate the air-side and water-side components of the UA using correlations developed by Holmes (1982). This approach requires some geometrical information about the coil and the paper investigates the sensitivity of the overall performance prediction to uncertainties in this information, including assuming a fixed ratio of air-side to water-side UA at the rating condition. Finally, simulation results from different coil models are compared, and experimental data are used to validate the improved cooling coil model.

Space heating represents the largest end use in the U.S. buildings and consumes more than 7 trillion Joules of site energy annually [USDOE]. Analyzing building space heating performance and identifying methods for saving energy are quite important. Hence, it is crucial to identify and evaluate key driving factors to space heating energy use to support the design and operation of low energy buildings.

In this study, the prototypical small and large-size office buildings of the USDOE commercial reference buildings, which comply with ASHRAE Standard 90.1-2004, are selected. Key design and operation factors were identified to evaluate their degrees of impact for space heating energy use. Simulation results demonstrate that some of the selected building design and operation parameters have more significant impacts on space heating energy use than others, on the other hand, good operation practice can save more space heating energy than raising design efficiency levels of an office building. Influence of weather data used in simulations on space heating energy is found to be significant. The simulated space heating energy use is further benchmarked against those from similar office buildings in two U.S. commercial buildings databases to better understand the discrepancies.

Simulated results from this study and space heating energy use collected from building databases can both vary in two potentially well overlapped wide ranges depending on details of building design and operation, not necessarily that simulation always under-predicts the reality.

For building energy simulation tools to be accessible to designers, tool interfaces should present a conventional view of HVAC systems to the user, and then map this view to the internal data model used in the tool. The paper outlines a process that enables design engineers to create HVAC system representations using industry standard terminology and system, icon and typological representations and convert that unified representation into the format required by the whole building energy simulation tool EnergyPlus. This paper describes each stage of the conversion process, which involves transformations between the following representations: 1) engineer's representation, 2) component connectivity representation, 3) representation in the internal data model used in the Simergy graphical user interface for EnergyPlus, and 4) EnergyPlus representation.

The paper also describes mappings between these representations and the development of a rule-based validation and assignment framework required to implement that mapping. In addition, the paper describes the implementation of this process in Simergy.

The performance of Heating, Ventilation and Air Conditioning (HVAC) systems may fail to satisfy design expectations due to improper equipment installation, equipment degradation, sensor failures, or incorrect control sequences. Commissioning identifies and implements cost-effective operational and maintenance measures in buildings to bring them up to the design intent or optimum operation. An existing office building is used as a case study to demonstrate the process of commissioning. Building energy benchmarking tools are applied to evaluate the energy performance for screening opportunities at the whole building level. A large natural gas saving potential was indicated by the building benchmarking results. Faulty operations in the HVAC systems, such as improper operations of air-side economizers, simultaneous heating and cooling, and ineffective optimal start, were identified through trend data analyses and functional testing. The energy saving potential for each commissioning measure is quantified with a calibrated building simulation model. An actual energy saving of 10% was realized after the implementations of cost-effective measures.

Existing buildings will dominate energy use in commercial buildings in the United States for three decades or longer and even in China for the about two decades. Retrofitting these buildings to improve energy efficiency and reduce energy use is thus critical to achieving the target of reducing energy use in the buildings sector. However there are few evaluation tools that can quickly identify and evaluate energy savings and cost effectiveness of energy conservation measures (ECMs) for retrofits, especially for buildings in China. This paper discusses methods used to develop such a tool and demonstrates an application of the tool for a retrofit analysis. The tool builds on a building performance database with pre-calculated energy consumption of ECMs for selected commercial prototype buildings using the EnergyPlus program. The tool allows users to evaluate individual ECMs or a package of ECMs. It covers building envelope, lighting and daylighting, HVAC, plug loads, service hot water, and renewable energy. The prototype building can be customized to represent an actual building with some limitations. Energy consumption from utility bills can be entered into the tool to compare and calibrate the energy use of the prototype building. The tool currently can evaluate energy savings and payback of ECMs for shopping malls in China. We have used the tool to assess energy and cost savings for retrofit of the prototype shopping mall in Shanghai. Future work on the tool will simplify its use and expand it to cover other commercial building types and other countries.

The Modelica Buildings library contains a package with a model for a thermal zone that computes heat transfer through the building envelope and within a room. It considers various heat transfer phenomena of a room, including conduction, convection, short-wave and long-wave radiation. The first part of this paper describes the physical phenomena considered in the room model. The second part validates the room model by using a standard test suite provided by the American Society of Heating, Refrigerating and Air-Conditioning Engineers (ASHRAE). The third part focuses on an application where the room model is used for simulation-based controls of a window shading device to reduce building energy consumption.

This paper describes the validation of the window model of the free open-source Modelica Buildings library. This paper starts by describing the physical modeling assumptions of the window model. The window model can be used to calculate the thermal and angular properties of glazing systems. It can also be used for steady-state simulation of heat transfer mechanism in glazing systems. We present simulation results obtained by comparing the window model with WINDOW 6 the well established simulation tool for steady-state heat transfer in glazing systems. We also present results obtained by comparing the window model with measurements carried out in a test cell at the Lawrence Berkeley National Laboratory.

This paper gives an overview of recent developments in the Building Controls Virtual Test Bed (BCVTB), a framework for co-simulation and hardware-in-the-loop.

First, a general overview of the BCVTB is presented. Second, we describe the BACnet interface, a link which has been implemented to couple BACnet devices to the BCVTB. We present a case study where the interface was used to couple a whole building simulation program to a building control system to assess in real-time the performance of a real building. Third, we present the ADInterfaceMCC, an analog/digital interface that allows a USB-based analog/digital converter to be linked to the BCVTB. In a case study, we show how the link was used to couple the analog/digital converter to a building simulation model for local loop control.

This paper reviews existing case studies and methods for calibrating whole building energy models to measured data. This research describes a systematic, evidence-based methodology for the calibration of these models. Under this methodology, parameter values in the final calibrated model reference the source of information used to make changes to the initial model. Thus, the final model is based solely on evidence. Version control software stores a complete record of the calibration process, and the evidence on which the final model is based. Future users can review the changes made throughout the calibration process along with the supporting evidence. In addition to the evidence-based methodology, this paper also describes a new zoning process that represents the real building more closely than the typical core and four perimeter zone approach. Though the methodology is intended to apply to detailed calibration studies with high resolution measured data, the primary aspects of the methodology (evidence-based approach, version control, and zone-typing) are independent of the available measured data.

This article describes the implementation of the Building Controls Virtual Test Bed (BCVTB). The BCVTB is a software environment that allows connecting different simulation programs to exchange data during the time integration, and that allows conducting hardware in the loop simulation. The software architecture is a modular design based on Ptolemy II, a software environment for design and analysis of heterogeneous systems. Ptolemy II provides a graphical model building environment, synchronizes the exchanged data and visualizes the system evolution during run-time. The BCVTB provides additions to Ptolemy II that allow the run-time coupling of different simulation programs for data exchange, including EnergyPlus, MATLAB, Simulink and the Modelica modelling and simulation environment Dymola. The additions also allow executing system commands, such as a script that executes a Radiance simulation. In this article, the software architecture is presented and the mathematical model used to implement the co-simulation is discussed. The simulation program interface that the BCVTB provides is explained. The article concludes by presenting applications in which different state of the art simulation programs are linked for run-time data exchange. This link allows the use of the simulation program that is best suited for the particular problem to model building heat transfer, HVAC system dynamics and control algorithms, and to compute a solution to the coupled problem using co-simulation.

Most commercial buildings do not perform as well in practice as intended by the design and their performances often deteriorate over time. Reasons include faulty construction, malfunctioning equipment, incorrectly configured control systems and inappropriate operating procedures (Haves et al., 2001, Lee et al., 2007). To address this problem, the paper presents a simulation-based whole building performance monitoring tool that allows a comparison of building actual performance and expected performance in real time. The tool continuously acquires relevant building model input variables from existing Energy Management and Control System (EMCS). It then reports expected energy consumption as simulated of EnergyPlus. The Building Control Virtual Test Bed (BCVTB) is used as the software platform to provide data linkage between the EMCS, an EnergyPlus model, and a database. This paper describes the integrated real-time simulation environment. A proof-of-concept demonstration is also presented in the paper.

At the Modelica 2009 conference, we introduced the Buildings library, a freely available Modelica library for building energy and control systems [16]. This paper reports the updates of the library and presents example applications for a range of heating, ventilation and air conditioning (HVAC) systems. Over the past two years, the library has been further developed. The number of HVAC components models has been doubled and various components have been revised to increase numerical robustness. The paper starts with an overview of the library architecture and a description of the main packages. To demonstrate the features of the Buildings library, applications that include multizone airow simulation as well as supervisory and local loop control of a variable air volume (VAV) system are briey described. The paper closes with a discussion of the current development.

Many inadequacies exist within industry-standard data models as used by present-day whole-building energy simulation software. Tools such as EnergyPlus and DOE-2 use custom schema definitions (IDD and BDL respectively) as opposed to standardized schema definitions (defined in XSD, EXPRESS, etc.). Non-standard data modes lead to a requirement for application developers to develop bespoke interfaces. Such tools have proven to be error prone in their implementation – typically resulting in information loss.

This paper presents a Simulation Domain Model (SimModel) - a new interoperable XML-based data model for the building simulation domain. SimModel provides a consistent data model across all aspects of the building simulation process, thus preventing information loss. The model accounts for new simulation tool architectures, existing and future systems, components and features. In addition, it is a multi-representation model that enables integrated geometric and MEP simulation configuration data. The SimModel objects ontology moves away from tool-specific, non-standard nomenclature by implementing an industry-validated terminology aligned with Industry Foundation Classes (IFC).

The first implementation of SimModel supports translations from IDD, Open Studio IDD, gbXML and IFC. In addition, the EnergyPlus Graphic User Interface (GUI) employs SimModel as its internal data model. Ultimately, SimModel will form the basis for a new IFC Model View Definition (MVD) that will enable data exchange from HVAC Design applications to Energy Analysis applications. Extensions to SimModel could easily support other data formats and simulations (e.g. Radiance, COMFEN, etc.).

Building energy performance is often inadequate when compared to design goals. To link design goals to actual operation one can compare measured with simulated energy performance data. Our previously developed comparison approach is the Energy Performance Comparison Methodology (EPCM), which enables the identification of performance problems based on a comparison of measured and simulated performance data. In context of this method, we developed a software tool that provides graphing and data processing capabilities of the two performance data sets. The software tool called SEE IT (Stanford Energy Efficiency Information Tool) eliminates the need for manual generation of data plots and data reformatting. SEE IT makes the generation of time series, scatter and carpet plots independent of the source of data (measured or simulated) and provides a valuable tool for comparing measurements with simulation results. SEE IT also allows assigning data points on a predefined building object hierarchy and supports different versions of simulated performance data. This paper briefly introduces the EPCM, describes the SEE IT tool and illustrates its use in the context of a building case study.

Demand controlled ventilation (DCV) was evaluated for general office spaces in California. A medium size office building meeting the prescriptive requirements of the 2008 California building energy efficiency standards (CEC 2008) was assumed in the building energy simulations performed with the EnergyPlus program to calculate the DCV energy savings potential in five typical California climates. Three design occupancy densities and two minimum ventilation rates were used as model inputs to cover a broader range of design variations. The assumed values of minimum ventilation rates in offices without DCV, based on two different measurement methods, were 81 and 28 cfm per occupant. These rates are based on the co‐author's unpublished analyses of data from EPA's survey of 100 U.S. office buildings. These minimum ventilation rates exceed the 15 to 20 cfm per person required in most ventilation standards for offices. The cost effectiveness of applying DCV in general office spaces was estimated via a life cycle cost analyses that considered system costs and energy cost reductions. The results of the energy modeling indicate that the energy savings potential of DCV is largest in the desert area of California (climate zone 14), followed by Mountains (climate zone 16), Central Valley (climate zone 12), North Coast (climate zone 3), and South Coast (climate zone 6). The results of the life cycle cost analysis show DCV is cost effective for office spaces if the typical minimum ventilation rates without DCV is 81 cfm per person, except at the low design occupancy of 10 people per 1000 ft2 in climate zones 3 and 6. At the low design occupancy of 10 people per 1000 ft2, the greatest DCV life cycle cost savings is a net present value (NPV) of $0.52/ft2 in climate zone 14, followed by $0.32/ft2 in climate zone 16 and $0.19/ft2 in climate zone 12. At the medium design occupancy of 15 people per 1000 ft2, the DCV savings are higher with a NPV $0.93/ft2 in climate zone 14, followed by $0.55/ft2 in climate zone 16, $0.46/ft2 in climate zone 12, $0.30/ft2 in climate zone 3, $0.16/ft2 in climate zone 3. At the high design occupancy of 20 people per 1000 ft2, the DCV savings are even higher with a NPV $1.37/ft2 in climate zone 14, followed by $0.86/ft2 in climate zone 16, $0.84/ft2 in climate zone 3, $0.82/ft2 in climate zone 12, and $0.65/ft2 in climate zone 6. DCV was not found to be cost effective if the typical minimum ventilation rate without DCV is 28 cfm per occupant, except at high design occupancy of 20 people per 1000 ft2 in climate zones 14 and 16. Until the large uncertainties about the base case ventilation rates in offices without DCV are reduced, the case for requiring DCV in general office spaces will be a weak case.

There is an increasing interest in the use of computer algorithms to identify combinations of parameters which optimize the energy performance of buildings. For such problems, the objective function can be multi-modal and needs to be approximated numerically using building energy simulation programs. As these programs contain iterative solution algorithms, they introduce discontinuities in the numerical approximation to the objective function. Metaheuristics often work well for such problems, but their convergence to a global optimum cannot be established formally. Moreover, different algorithms tend to be suited to particular classes of optimization problems. To shed light on this issue we compared the performance of two metaheuristics, the hybrid CMA-ES/HDE and the hybrid PSO/HJ, in minimizing standard benchmark functions and real-world building energy optimization problems of varying complexity. From this we find that the CMA-ES/HDE performs well on more complex objective functions, but that the PSO/HJ more consistently identifies the global minimum for simpler objective functions. Both identified similar values in the objective functions arising from energy simulations, but with different combinations of model parameters. This may suggest that the objective function is multi-modal. The algorithms also correctly identified some non-intuitive parameter combinations that were caused by a simplified controls sequence of the building energy system that does not represent actual practice, further reinforcing their utility.

VL - 3
IS - 2
ER -
TY - JOUR
T1 - Co-simulation for performance prediction of integrated building and HVAC systems - An analysis of solution characteristics using a two-body system
JF - Simulation Modelling Practice and Theory
Y1 - 2010
A1 - Marija Trcka
A1 - Jan Hensen
A1 - Michael Wetter
AB - Integrated performance simulation of buildings and heating, ventilation and air-conditioning (HVAC) systems can help in reducing energy consumption and increasing occupant comfort. However, no single building performance simulation (BPS) tool offers sufficient capabilities and flexibilities to analyze integrated building systems and to enable rapid prototyping of innovative building and system technologies. One way to alleviate this problem is to use co-simulation to integrate different BPS tools. Co-simulation approach represents a particular case of simulation scenario where at least two simulators solve coupled differential-algebraic systems of equations and exchange data that couples these equations during the time integration. This article analyzes how co-simulation influences consistency, stability and accuracy of the numerical approximation to the solution. Consistency and zero-stability are studied for a general class of the problem, while a detailed consistency and absolute stability analysis is given for a simple two-body problem. Since the accuracy of the numerical approximation to the solution is reduced in co-simulation, the article concludes by discussing ways for how to improve accuracy.
VL - 18
IS - 7
ER -
TY - Generic
T1 - Development and Testing of Model Predictive Control for a Campus Chilled Water Plant with Thermal Storage
T2 - 2010 ACEEE Summer Study on Energy Efficiency in Buildings
Y1 - 2010
A1 - Brian E. Coffey
A1 - Philip Haves
A1 - Michael Wetter
A1 - Brandon Hencey
A1 - Francesco Borrelli
A1 - Yudong Ma
A1 - Sorin Bengea
AB -

A Model Predictive Control (MPC) implementation was developed for a university campus chilled water plant. The plant includes three water-cooled chillers and a two million gallon chilled water storage tank. The tank is charged during the night to minimize on-peak electricity consumption and take advantage of the lower ambient wet bulb temperature. A detailed model of the chilled water plant and simplified models of the campus buildings were developed using the equation-based modeling language Modelica. Steady state models of the chillers, cooling towers and pumps were developed, based on manufacturers' performance data, and calibrated using measured data collected and archived by the control system. A dynamic model of the chilled water storage tank was also developed and calibrated. A semi-empirical model was developed to predict the temperature and flow rate of the chilled water returning to the plant from the buildings. These models were then combined and simplified for use in a MPC algorithm that determines the optimal chiller start and stop times and set-points for the condenser water temperature and the chilled water supply temperature. The paper describes the development and testing of the MPC implementation and discusses lessons learned and next steps in further research.

This paper presents a new approach to model air flows with a zonal model. The aim of zonal models is to perform quick simulations of the air distribution in rooms. Therefore an air volume is subdivided into several discrete zones, typically 10 to 100. The zones are connected with flow elements computing the amount of air exchanged between them. In terms of complexity and needed computational time zonal models are a compromise between CFD calculations and the approximation of perfect mixing. In our approach the air flow velocity is used as property of the zones. Thus the distinction between normal zones and jet or plume influenced zones becomes obsolete. The model is implemented in the object oriented and equation based language Modelica. A drawback of the new formulation is that the calculated flow pattern depends on the discretization. Nevertheless, the results show that the new zonal model performs well and is a useful extension to existing models.

This paper reviews findings from research conducted at a university campus to develop a robust systems approach to monitor and continually optimize building energy performance. The field analysis, comprising three projects, included detailed monitoring, model-based analysis of system energy performance, and implementation of optimized control strategies for both district and building-scale systems. One project used models of the central cooling plant and campus building loads, and weather forecasts to analyze and optimize the energy performance of a district cooling system, comprising chillers, pumps and a thermal energy storage system. Fullscale implementation of policies devised with a model predictive control approach produced energy savings of about 5%, while demonstrating that the heuristic policies implemented by the operators were close to optimal during peak cooling season and loads. Research was also conducted to evaluate whole building monitoring and control methods. A second project performed in a campus building combined sub-metered end-use data, performance benchmarks, energy simulations and thermal load estimators to create a web-based energy performance visualization tool prototype. This tool provides actionable energy usage information to aid in facility operation and to enable performance improvement. In a third project, an alternative to demand controlled ventilation enabled by direct measurements of building occupancy levels was assessed. Simulations were used to show 5-15% reduction in building HVAC system energy usage when using estimates of actual occupancy levels.

Numerical predictions with a differential Reynolds stress closure, which in its original formulation explicitly takes into account possible states of turbulence on the anisotropy-invariant map, are presented. Thus the influence of anisotropy of turbulence on the modeled terms in the governing equations for the Reynolds stresses is accounted for directly. The anisotropy invariant Reynolds stress model (AIRSM) is implemented and validated in different finite-volume codes. The standard wall-function approach is employed as initial step in order to predict simple and complex wall-bounded flows undergoing large separation. Despite the use of simple wall functions, the model performed satisfactory in predicting these flows. The predictions of the AIRSM were also compared with existing Reynolds stress models and it was found that the present model results in improved convergence compared with other models. Numerical issues involved in the implementation and application of the model are also addressed.

The application of software tools for moisture protection of buildings in different climatic zones is demonstrated in this paper. The basics of the programs are presented together with a typical application for a problem specific for the chosen climatic zone. A 1-D calculation has been performed for tropical climate zone with the improvement of a flat roof in Bangkok as an example. For half timbered buildings, which are common in the temperate zone with the 2-D model an infill insulation and its benefits are demonstrated. Finally the combined appliance of the whole building model and the mould risk prognosis model is shown in detail as a special case for the cold climate zone: In heated buildings of cold climate zones the internal climate with its low relative humidity in wintertime often causes discomfort and health problems for the occupants. In case of using air humidifier the risk of mould growth increases. Instead of an uncontrolled humidifying of the dry air an innovativecontrol system using a thermal bridge, which switches the humidifier off when condensation occurs is presented. To quantify the improvement in the comfort while preventing the risk of mould growth for a typical building comparative calculations of the resulting inner climates and its consequences on comfort have been performed.

The Continuous Commissioning Leading Project (CCLEP) process is an ongoing process to apply system optimization theory and advanced technologies to commercial retrofit projects. It was developed by Liu et al (2006) through a U.S. Department of Energy grant to the University of Nebraska and the Omaha Public Power District (OPPD) for continuous commissioning applications in commercial retrofit projects. The CCLEP process, procedures and seven case study results have already been presented (Liu et al 2006).

CCLEP was applied to a luxury shopping mall and office building. The case study building has ten single fan dual-duct VAV AHUs, 123 dual-duct pneumatic controller pressure independent terminal boxes, and a central heating and cooling plant. Major retrofit efforts include upgrading pneumatic to DDC controls for all AHUs, installing main hot deck dampers, replacing the boiler, installing VFD on fans and pumps, and installing Fan Airflow Stations (FAS) and Pump Waterflow Stations (PWS). This paper presents the optimal control strategies, which include main hot deck damper control, supply fan control integrated with FAS, return fan control, optimal control for terminal boxes, chilled water temperature and chilled water pump speed control, hot water temperature and hot water pump control. The measured hourly utility data after CCLEP show that annual HVAC electricity consumption is reduced by 56% and gas use is reduced by 36%.

This paper demonstrates the energy savings and system performance improvement through retrofits and optimal system control. This paper will present the case study building information, CCLEP major retrofits, CCLEP optimal control strategies, CCLEP results and conclusions

This paper takes a close look at the China national standard GB50189-2005, Design Standard for Energy Efficiency of Public Buildings, which was enforced on July 1, 2005. The paper first reviews the standard, then compares the standard with ASHRAE Standard 90.1-2004 to identify discrepancies in code coverage and stringency, and recommends some energy conservation measures that can be evaluated in the design of public buildings to achieve energy savings beyond the standard. The paper also highlights several important features of 90.1-2004 that may be considered as additions to the GB50189-2005 standard during the next revision. At the end the paper summarizes the latest developments in building energy standards and rating systems in China and the US.

With the current movement towards net zero energy buildings, many technologies are promoted with emphasis on their superior energy efficiency. The variable refrigerant flow (VRF) and ground source heat pump (GSHP) systems are probably the most competitive technologies among these. However, there are few studies reporting the energy efficiency of VRF systems compared with GSHP systems. In this article, a preliminary comparison of energy efficiency between the air-source VRF and GSHP systems is presented. The computer simulation results show that GSHP system is more energy efficient than the air-source VRF system for conditioning a small office building in two selected US climates. In general, GSHP system is more energy efficient than the air-source VRV system, especially when the building has significant heating loads. For buildings with less heating loads, the GSHP system could still perform better than the air-source VRF system in terms of energy efficiency, but the resulting energy savings may be marginal.

Integrated performance simulation of buildings HVAC systems can help in reducing energy consumption and increasing occupant comfort. However, no single building performance simulation (BPS) tool offers sufficient capabilities and flexibilities to analyze integrated building systems and to enable rapid prototyping of innovative building and system technologies. One way to alleviate this problem is to use co-simulation, as an integrated approach to simulation. This article elaborates on issues important for co-simulation realization and discusses multiple possibilities to justify the particular approach implemented in the here described co-simulation prototype. The prototype is validated with the results obtained from the traditional simulation approach. It is further used in a proof-of-concept case study to demonstrate the applicability of the method and to highlight its benefits. Stability and accuracy of different coupling strategies are analyzed to give a guideline for the required coupling time step.

A software tool that automates the analysis of functional tests for air-handling units is described. The tool compares the performance observed during manual tests with the performance predicted by simple models of the components under test that are configured using design information and catalog data. Significant differences between observed and expected performance indicate the presence of faults. Fault diagnosis is performed by analyzing the variation of these differences with operating point using expert rules and fuzzy inferencing.

The tool has a convenient user interface to facilitate manual entry of measurements made during a test. A graphical display compares the measured and expected performance, highlighting significant differences that indicate the presence of faults. The tool is designed to be used by commissioning providers conducting functional tests as part of either new building commissioning or retro-commissioning, as well as by building owners and operators conducting routine tests to check the performance of their HVAC systems. The paper describes the input data requirements of the tool, the software structure, the graphical interface, and summarizes the development and testing process used.

VL - 113
U1 -

Simulation Research Group

U2 - LBNL-2077E
ER -
TY - Generic
T1 - High performance computing for indoor air
T2 - 11th International IBPSA Conference (Building Simulation 2009)
Y1 - 2009
A1 - Wangda Zuo
A1 - Qingyan Chen
JF - 11th International IBPSA Conference (Building Simulation 2009)
CY - Glasgow, U.K.
ER -
TY - Generic
T1 - An implementation of co-simulation for performance prediction of innovative integrated HVAC systems in buildings
T2 - Proc. of the 11th IBPSA Conference
Y1 - 2009
A1 - Marija Trcka
A1 - Michael Wetter
A1 - Jan Hensen
AB - Integrated performance simulation of buildings and heating, ventilation and air-conditioning (HVAC)systems can help reducing energy consumption and increasing level of occupant comfort. However, no singe building performance simulation (BPS) tool offers sufficient capabilities and flexibilities to accommodate the ever-increasing complexity and rapid innovations in building and system technologies. One way to alleviate this problem is to use co-simulation. The co-simulation approach represents a particular case of simulation scenario where at least two simulators solve coupled differential-algebraic systems of equations and exchange data that couples these equations during the time integration. This paper elaborates on issues important for co-simulation realization and discusses multiple possibilities to justify the particular approach implemented in a co-simulation prototype. The prototype is verified and validated against the results obtained from the traditional simulation approach. It is further used in a case study for the proof-of-concept, to demonstrate the applicability of the method and to highlight its benefits. Stability and accuracy of different coupling strategies are analyzed to give a guideline for the required coupling frequency. The paper concludes by defining requirements and recommendations for generic co-simulation implementations.
JF - Proc. of the 11th IBPSA Conference
CY - Glasgow, Scotland
UR - http://www.ibpsa.org/proceedings/BS2009/BS09_0724_731.pdf
ER -
TY - JOUR
T1 - Improving Control and Operation of a Single Duct VAV System through CCLEP
JF - ASHRAE Transactions
Y1 - 2009
A1 - Young-Hum Cho
A1 - Mingsheng Liu
A1 - Xiufeng Pang
AB -

With the energy crisis of the early 1970s came the realization that buildings could be made much more efficient without sacrificing comfort. Over the last 30 years, use of variable air volume systems has become common practice. Many variable air volume (VAV) systems with pneumatic controls were installed in the 1980s and are still in use. However, these systems often have outdated control strategies and deficient mechanical systems are deficient, which may cause occupant discomfort and excess energy consumption.

An ASHRAE committee proposed building commissioning in 1988 to ensure that system performance met design specifications. Continuous Commissioning (CC[R]) technology was developed and implemented in 1992. CC is an ongoing process to resolve operating problems, improve comfort, optimize energy use and identify retrofits for existing commercial and institutional buildings and central plant facilities [1-5]. Since 1999, the Energy Systems Laboratory (ESL) at the University of Nebraska has conducted extensive research to implement optimal system control during the design phase and finalize the optimal setpoints after system installation. ESL researchers have developed and implemented the Continuous Commissioning Leading Energy Project (CCLEP) process with federal and industry support. The CCLEP process has two stages: the contracting stage and the implementation stage. During the contracting stage, a comprehensive technical evaluation is performed. The CCLEP implementation stage involves planning, retrofit and trouble shooting, and optimization and follow-up. The CCLEP process, procedures and seven case study results are presented in [6].

This paper presents information on the case study facility, existing and improved control sequences, and building performance improvement and energy consumption measures before and after CCLEP implementation

This paper presents the Key Factors methodology that supports energy managers in determining the optimal building operation strategy in relation to both energy consumption and thermal comfort. The methodology is supported by the utilisation of calibrated building energy simulation models that match measured data gathered by an extensive measurement framework. The paper outlines the proposed methodology defining the underpinning concepts and illustrating the performance metrics required to capture the effect of different building operation strategies. A brief case study is discussed to demonstrate the application of the methodology.

The Buildings library is a freely available Modelica library that is based on Modelica.Fluid. It contains component models for building heating, ventilation and air conditioning systems. It also contains an interface that allows co-simulation with the Ptolemy software framework for concurrent, real-time, embedded systems developed by the University of California at Berkeley. The primary applications are controls design, energy analysis and model-based operation. The library has been used to model hydronic space heating systems, variable air volume flow systems and it has been linked to the EnergyPlus building energy simulation program for co-simulation using Ptolemy II. The library contains dynamic and steady-state component models that are applicable for analyzing fast transients when designing control algorithms and for conducting annual simulations when assessing energy performance. For most models, dimensional analysis is used to compute the performance for operating points that differ from nominal conditions. This allows parameterizing models in the absence of detailed geometrical information which is often impractical to obtain during the conceptual design phase of building systems.

This paper describes an open-source library with component models for building energy and control systems that is based on Modelica, an equation-based object oriented language that is well positioned to become the standard for modeling of dynamic systems in various industrial sectors. The library is currently developed to support computational science and engineering for innovative building energy and control systems. Early applications will include controls design and analysis, rapid prototyping to support innovation of new building systems and the use of models during operation for controls, fault detection and diagnostics. This paper discusses the motivation for selecting an equation-based object-oriented language. It presents the architecture of the library and explains how base model scan be used to rapidly implement new models. To demonstrate the capability of analyzing novel energy and control systems, the paper closes with an example where we compare the dynamic performance of a conventional hydronic heating system with thermostatic radiator valves to an innovative heating system. In the new system, instead of a centralized circulation pump, each of the 18 radiators has a pump whose speed is controlled using a room temperature feedback loop, and the temperature of the boiler is controlled based on the speed of the radiator pump. All flows are computed by solving for the pressure distribution in the piping network, and the controls include continuous and discrete time controls.

This paper describes the origin, structure and continuing development of a model of time varying energy consumption in the US commercial building stock. The model is based on a flexible structure that disaggregates the stock into various categories (e.g. by building type, climate, vintage and life-cycle stage) and assigns attributes to each of these (e.g. floor area and energy use intensity by fuel type and end use), based on historical data and user-defined scenarios for future projections. In addition to supporting the interactive exploration of building stock dynamics, the model has been used to study the likely outcomes of specific policy and innovation scenarios targeting very low future energy consumption in the building stock. Model use has highlighted the scale of the challenge of meeting targets stated by various government and professional bodies, and the importance of considering both new construction and existing buildings.

The paper describes work to enable improved energy performance of existing and new retail stores belonging to a national chain and thereby also identify measures and tools that would improve the performance of ‘big box' stores generally. A detailed energy simulation model of a standard store design was developed and used to:

demonstrate the benefits of benchmarking the energy performance of retail stores of relatively standard design using baselines derived from simulation,

identify cost-effective improvements in the efficiency of components to be incorporated in the next design cycle,

use simulation to identify potential control strategy improvements that could be adopted in all stores, improving operational efficiency.

The core enabling task of the project was to develop an energy model of the current standard design using the EnergyPlus simulation program. For the purpose of verification of the model against actual utility bills, the model was reconfigured to represent twelve existing stores (seven relatively new stores and five older stores) in different US climates and simulations were performed using weather data obtained from the National Weather Service. The results of this exercise, which showed generally good agreement between predicted and measured total energy use, suggest that dynamic benchmarking based on energy simulation would be an effective tool for identifying operational problems that affect whole building energy use. The models of the seven newer stores were then configured with manufacturers' performance data for the equipment specified in the current design and used to assess the energy and cost benefits of increasing the efficiency of selected HVAC, lighting and envelope components. The greatest potential for cost-effective energy savings appears to be a substantial increase in the efficiency of the blowers in the roof top units and improvements in the efficiency of the lighting. The energy benefits of economizers on the roof-top units were analyzed and found to be very sensitive to the operation of the exhaust fans used to control building pressurization.

This paper presents an approach to comparing computer run time of building simulation programs. The computing run time of a simulation program depends on several key factors, including the calculation algorithm and modeling capabilities of the program, the run period, the simulation time step, the complexity of the energy models, the run control settings, and the software and hardware configurations of the computer that is used to make the simulation runs. To demonstrate the approach, simulation runs are performed for several representative DOE-2.1E and EnergyPlus energy models. The computer run time of these energy models are then compared and analyzed.

Wireless Building Management Systems (BMS) are an attractive option when it comes to building retrofitting due to the cost constraints introduced by wired systems. A crucial part of the wireless BMS is the initial planning stage, this process can be impossible for a designer to undertake, therefore highlighting the requirement for a software design tool to aid in this process.

This paper describes the Building Controls Virtual Test Bed (BCVTB) that is currently under development at Lawrence Berkeley National Laboratory. An earlier prototype linked EnergyPlus with controls hardware through embedded SPARK models and demonstrated its value in more cost-effective envelope design and improved controls sequences for the San Francisco Federal Building. The BCVTB presented here is a more modular design based on a middleware that we built using Ptolemy II, a modular software environment for design and analysis of heterogeneous systems. Ptolemy II provides a graphical model building environment, synchronizes the exchanged data and visualizes the system evolution during run-time. Our additions to Ptolemy II allow users to couple to Ptolemy II a prototype version of EnergyPlus, MATLAB/Simulink or other simulation programs for data exchange during run-time. In future work we will also implement a BACnet interface that allows coupling BACnet compliant building automation systems to Ptolemy II. We will present the architecture of the BCVTB and explain how users can add their own simulation programs to the BCVTB. We will then present an example application in which the building envelope and the HVAC system was simulated in EnergyPlus, the supervisory control logic was simulated in MATLAB/Simulink and Ptolemy II was used to exchange data during run-time and to provide real-time visualization as the simulation progresses.

The indoor temperature and humidity conditions of the building envelope are important parameters for the evaluation of the thermal and hygric indoor comfort. In the research project GENSIM a new hygrothermal building library, based on the object- and equation-oriented model description language Modelica® has been developed by the Fraunhofer Institutes IBP and FIRST. This library includes many models as for instance a hygrothermal wall model, an air volume model, a zone model, a window model and an environment model. Due to the object-oriented modelling approach, some models of this library can be configured to a complex hygrothermal room model, which can predict the time dependent indoor temperature and humidity conditions in a building construction. In this paper we will introduce in a first step the object-oriented hygrothermal room model of this library. In a second step, the validation of the room model with some field experiments will be shown. In a third step we willpresent some simulation results, we obtained by coupling the room model with an implemented Predicted-Mean-Vote (PMV) control ventilation system to predict and to ensure a thermal and hygric indoor comfort in one case study. In the conclusion, the possible range of future applications of this new hygrothermal building physics library and demands for further research are indicated.

In fault detection and diagnostics, limitations coming from the sensor network architecture are one of the main challenges in evaluating a system's health status. Usually the design of the sensor network architecture is not solely based on diagnostic purposes, other factors like controls, financial constraints, and practical limitations are also involved. As a result, it quite common to have one sensor (or one set of sensors) monitoring the behaviour of two or more components. This can significantly extend the complexity of diagnostic problems. In this paper a systematic approach is presented to deal with such complexities. It is shown how the problem can be formulated as a Bayesian network based diagnostic mechanism with latent variables. The developed approach is also applied to the problem of fault diagnosis in HVAC systems, an application area with considerable modeling and measurement constraints.

The 2007 Florida Building Code (ICC, 2008) requires building designers and architects to achieve a minimum energy efficiency rating for commercial buildings located throughout Florida. Although the Florida Building Code is strict in the minimum requirements for new construction, several aspects of building construction can be further improved through careful thought and design. This report outlines several energy saving features that can be used to ensure that new buildings meet a new target goal of 85% energy use compared to the 2007 energy code in order to achieve Governor Crist's executive order to improve the energy code by 15%.

To determine if a target goal of 85% building energy use is attainable, a computer simulation study was performed to determine the energy saving features available which are, in most cases, stricter than the current Florida Building Code. The energy savings features include improvements to building envelop, fenestration, lighting and equipment, and HVAC efficiency. The imp acts of reducing outside air requirements and employing solar water heating were also investigated. Th e purpose of the energy saving features described in this document is intended to provide a simple, prescriptive method for reducing energy consumption using the methodology outlined in ASHRAE Standard 90.1 (ASHRAE, 2007).

There are two difficulties in trying to achieve savings in non-residential structures. First, there is significant energy use caused by internal loads for people and equipment and it is difficult to use the energy code to achieve savings in this area relative to a baseline. Secondly, the ASHRAE methodology uses some of the same features that are proposed for the new building, so it may be difficult to claim savings for some strategies that will produce savings such as improved ventilation controls, reduced window area, or reduced plug loads simply because the methodology applies those features to the comparison reference building.

Several measures to improve the building envelope characteristics were simulated. Simply using the selected envelope measures resulted in savings of less than 10% for all building types. However, if such measures are combined with aggressive lighting reductions and improved efficiency HVAC equipment and controls, a target savings of 15% is easily attainable.

Modelica is an object-oriented acausal modeling language that is well positioned to become a de-facto standard for expressing models of complex physical systems. To simulate a model expressed in Modelica, it needs to be translated into executable code. For generating run-time efficient code, such a translation needs to employ algebraic formula manipulations. As the SPARK solver has been shown to be competitive for generating such code but currently cannot be used with the Modelica language, we report in this paper how SPARK's symbolic and numerical algorithms can be implemented in OpenModelica, an open-source implementation of a Modelica modeling and simulation environment. We also report benchmark results that show that for our air flow network simulation benchmark, the SPARK solver is competitive with Dymola, which is believed to provide the best solver for Modelica.

A software tool that automates the analysis of functional tests for air-handling units is described. The tool compares the performance observed during manual tests with the performance predicted by simple models of the components under test that are configured using design information and catalog data. Significant differences between observed and expected performance indicate the presence of faults. Fault diagnosis is performed by analyzing the variation of these differences with operating point using expert rules and fuzzy inferencing.

The tool has a convenient user interface to facilitate manual entry of measurements made during a test. A graphical display compares the measured and expected performance, highlighting significant differences that indicate the presence of faults. The tool is designed to be used by commissioning providers conducting functional tests as part of either new building commissioning or retro-commissioning, as well as by building owners and operators conducting routine tests to check the performance of their HVAC systems. The paper describes the input data requirements of the tool, the software structure, the graphical interface, and summarizes the development and testing process used.

The services sector has the least amount of energy end use data available, which poses significant challenges to companies within the sector attempting to benchmark their energy performance and inform energy management decisions. This paper explores through a case study analysis the use of simple performance indicators and how additional data and new metrics can greatly enhance the understanding of energy trends and in particular the assessment of building energy performance. The country chosen for the analysis is Ireland, where the services sector has experienced high energy demand growth since 1990 (4.1% annually) compared with the EU-15 (1.5% annually). Despite this growth, the available energy data is poor, in particular for the public service sub-sectors. The case study chosen is an institution within the education sub-sector, University College Cork. The paper presents some simple energy performance indicators that have been used to date to inform energy policy. The paper then introduces new approaches and tools for assessing energy performance in buildings and how these may be utilised to improve the energy policy decision making and energy management. It discusses how these approaches are been implemented for buildings with separate functions, presents some initial results and discusses future planned work.

The temperature oscillation technique to measure the thermal diffusivity of a fluid consists of filling a cylindrical volume with the fluid, applying an oscillating temperature boundary condition at the two ends of the cylinder, measuring the amplitude and phase of the temperature oscillation at any point inside the cylinder, and finally calculating the fluid thermal diffusivity from the amplitude and phase values of the temperature oscillations at the ends and at the point inside the cylinder. Although this experimental technique was introduced by Santucci and co-workers nearly two decades ago, its application is still limited, perhaps because of the perceived difficulties in obtaining accurate results. Here, we attempt to clarify this approach by first estimating the maximum size of the liquid’s cylindrical volume, performing a systematic series of experiments to find the allowable amplitude and frequency of the imposed temperature oscillations, and then validating our experimental setup and the characterization method by measuring the thermal conductivity of pure water at different temperatures and comparing our results with previously published work.

The temperature oscillation technique to measure the thermal diffusivity of a fluid consists of filling a cylindrical volume with the fluid, applying an oscillating temperature boundary condition at the two ends of the cylinder, measuring the amplitude and phase of the temperature oscillation at any point inside the cylinder, and finally calculating the fluid thermal diffusivity from the amplitude and phase values of the temperature oscillations at the ends and at the point inside the cylinder. Although this experimental technique was introduced by Santucci and co-workers nearly two decades ago, its application is still limited, perhaps because of the perceived difficulties in obtaining accurate results. Here, we attempt to clarify this approach by first estimating the maximum size of the liquid’s cylindrical volume, performing a systematic series of experiments to find the allowable amplitude and frequency of the imposed temperature oscillations, and then validating our experimental setup and the characterization method by measuring the thermal conductivity of pure water at different temperatures and comparing our results with previously published work.

Diverse air conditioning products with enhanced dehumidification features are being introduced to meet the increased moisture laden ventilation air requirements of ASHRAE Standard 62 in humid climates. In this evaluation, state point performance spreadsheet models for single path, mixed air packaged systems compare a conventional "off the shelf" direct expansion (DX) cooling system and its performance to systems that augment the DX coil with enhanced dehumidification components, such as heat exchangers and desiccant dehumidifiers. Using common performance metrics for comparisons at ARI rating conditions, these alternative systems define a best practice for enhanced dehumidification performance. The state point performance spreadsheet models combine available algorithms from the EnergyPlus™ simulation program for DX coils and heat exchangers with newly developed algorithms for desiccant dehumidifiers. All the models and their algorithms are applied in EnergyPlus™ for simulations of annual system cooling performance, including sensible and latent loads met, energy consumed, and humidity levels maintained, in select building types and climatic locations. Per this EnergyPlus™ analysis, these enhanced dehumidification systems present challenging decision-making tradeoffs between humidity control improvements over conventional DX systems, condensing (compressor) unit energy consumption reductions versus DX cool and reheat approaches, and fan energy use increases due to the additional component pressure drops.

The paper describes the development of a model specification for performance monitoring systems for commercial buildings. The specification focuses on four key aspects of performance monitoring: performance metrics measurement system requirements data acquisition and archiving data visualization and reporting The aim is to assist building owners in specifying the extensions to their control systems that are required to provide building operators with the information needed to operate their buildings more efficiently and to provide automated diagnostic tools with the information required to detect and diagnose faults and problems that degrade energy performance. The paper reviews the potential benefits of performance monitoring, describes the specification guide and discusses briefly the ways in which it could be implemented. A prototype advanced visualization tool is also described, along with its application to performance monitoring. The paper concludes with a description of the ways in which the specification and the visualization tool are being disseminated and deployed.

Thermal conductivity enhancement in nanofluids, which are liquids containing suspended nanoparticles, has been attributed to localized convection arising from the nanoparticles' Brownian motion. Because convection and mass transfer are similar processes, the objective here is to visualize dye diffusion in nanofluids. It is observed that dye diffuses faster in nanofluids compared to that in water, with a peak enhancement at a nanoparticle volume fraction, φ, of 0.5%. A possible change in the slope of thermal conductivity enhancement at that same φ signifies that convection becomes less important at higher φ. The enhanced mass transfer in nanofluids can be utilized to improve diffusion in microfluidic devices.

This paper describes a guide for specifying performance monitoring systems that was developed as part of jointly funded CEC PIER-DOE project intended to assist commercial and institutional building owners in specifying what is required to obtain the information necessary to initiate and sustain an ongoing commissioning activity. The project's goal was to facilitate the delivery of specific performance related information to the benefit of both commissioning providers and building operators. A number of large-building owners were engaged in order to help create 'market pull' for performance monitoring while producing a specification that met their needs. The specification guide and example specification language addresses four key aspects of performance monitoring:

performance metrics

measurement system requirements

data acquisition and archiving

data visualization and reporting

The paper describes key aspects of the guide including how measurement accuracy requirements relate to the performance metrics that are used in both troubleshooting and routine reporting. Guide development activities and related tech-transfer efforts are also presented.

The paper describes and documents a library of equipment reference models developed for automated fault detection and diagnosis of secondary HVAC system (air handling units and air distribution systems). The models are used to predict the performance that would be expected in the absence of faults. The paper includes a description of the use of automatic documentation methods in the library.

In July 1998, the U.S. Department of Energy (USDOE) and China's Ministry of Science of Technology (MOST) signed a Statement of Work (SOW) to collaborate on the design and construction of an energyefficient demonstration office building and design center to be located in Beijing. The proposed 13,000 m2 (140,000 ft2) nine-story office building would use U.S. energy-efficient materials, space-conditioning systems, controls, and design principles that were judged to be widely replicable throughout China. The SOW stated that China would contribute the land and provide for the costs of the base building, while the U.S. would be responsible for the additional (or marginal) costs associated with the package of energy efficiency andrenewable energy improvements to the building. The project was finished and the building occupied in 2004.

Using DOE-2 to analyze the energy performance of the as-built building, the building obtained 44 out of 69 possible points according to the Leadership in Energy and Environmental Design (LEED) rating, including the full maximum of 10 points in the energy performance section. The building achieved a LEED Gold rating, the first such LEED-rated office building in China, and is 60% more efficient than ASHRAE 90.1-1999. The utility data from the first year's operation match well the analysis results, providing that adjustments are made for unexpected changes in occupancy and operations. Compared with similarly equipped office buildings in Beijing, this demonstration building uses 60% less energy per floor area. However, compared to conventional office buildings with less equipment and window air-conditioners, the building uses slightly more energy per floor area.

We present the implementation of a library of multi-zone airflow models in Modelica and a comparative model validation with CONTAM. Our models have a similar level of detail as the models in CONTAM and COMIS. The multizone airflow models allow modeling the flow between rooms through doors, staircases or construction cracks. The flow can be caused by buoyancy effects, such as stack effects in high rise buildings or air temperature imbalance between adjoining rooms, by flow imbalance of a ventilation system, or by wind pressure on the building envelope. The here presented library can be used with a Modelica library for thermal building and HVAC system simulation to compute interzonal air flow rates. The combined use facilitates the integrated design of building systems, which is typically required for analyzing the interaction of room control loops in variable air volume flow systems through open doors, the flow in naturally ventilated buildings and the pressure in elevator shafts caused by stacked effects.

In the literature on generalized pattern search algorithms, convergence to a stationary point of a once continuously differentiable cost function is established under the assumption that the cost function can be evaluated exactly. However, there is a large class of engineering problems where the numerical evaluation of the cost function involves the solution of systems of differential algebraic equations. Since the termination criteria of the numerical solvers often depend on the design parameters, computer code for solving these systems usually defines a numerical approximation to the cost function that is discontinuous with respect to the design parameters. Standard generalized pattern search algorithms have been applied heuristically to such problems, but no convergence properties have been stated. In this paper we extend a class of generalized pattern search algorithms to include a subprocedure that adaptively controls the precision of the approximating cost functions. The numerical approximations to the cost function need not define a continuous function. Our algorithms can be used for solving linearly constrained problems with cost functions that are at least locally Lipschitz continuous. Assuming that the cost function is smooth, we prove that our algorithms converge to a stationary point. Under the weaker assumption that the cost function is only locally Lipschitz continuous, we show that our algorithms converge to points at which the Clarke generalized directional derivatives are nonnegative in predefined directions. An important feature of our adaptive precision scheme is the use of coarse approximations in the early iterations, with the approximation precision controlled by a test. We show by numerical experiments that such an approach leads to substantial time savings in minimizing computationally expensive functions.

For the past decade, the non-residential portion of California's Title-24 building energy standard has relied on DOE-2.1E as the reference computer simulation program for development as well as compliance. However, starting in 2004, the California Energy Commission has been evaluating the possible use of EnergyPlus as the reference program in future revisions of Title-24. As part of this evaluation, the authors converted the Alternate Compliance Method (ACM) certification test suite of 150 DOE-2 files to EnergyPlus, and made parallel DOE-2 and EnergyPlus runs for this extensive set of test cases. A customized version of DOE-2.1E named doe2ep was developed to automate the conversion process. This paper describes this conversion process, including the difficulties in establishing an apples-to-apples comparison between the two programs, and summarizes how the DOE-2 and EnergyPlus results compare for the ACM test cases.

We propose a simulation–precision control algorithm that can be used with a family of derivative free optimization algorithms to solve optimization problems in which the cost function is defined through the solutions of a coupled system of differential algebraic equations (DAEs). Our optimization algorithms use coarse precision approximations to the solutions of the DAE system in the early iterations and progressively increase the precision as the optimization approaches a solution. Such schemes often yield a significant reduction in computation time. We assume that the cost function is smooth but that it can only be approximated numerically by approximating cost functions that are discontinuous in the design parameters. We show that this situation is typical for many building energy optimization problems.We present a new building energy and daylighting simulation program, which constructs approximations to the cost function that converge uniformly on bounded sets to a smooth function as precision is increased.We prove that for our simulation program, our optimization algorithms construct sequences of iterates with stationary accumulation points. We present numerical experiments in which we minimize the annual energy consumption of an office building for lighting, cooling and heating. In these examples, our precision control algorithm reduces the computation time up to a factor of four.

Many existing building energy performance assessment frameworks, quantifying and categorising buildings post occupancy, offer limited feedback on design decisions. An environment providing decision makers with pertinent information to assess the consequences of each design decision in a timely, cost effective and practical manner is required to promote viable low-energy solutions from the outset. This paper outlines a performance-based strategy utilising building effectiveness communication ratios stored in Building Information Models (BIM). Decision makers will be capable of rating the building's energy performance throughout its natural life cycle without imposing adverse penalties on facilities located in dissimilar climatic zones subjected to stringent building codes and regulations. With this advancement in building energy assessment in place, a progressive improvement in energy efficiency for the building stock is a feasible and realistic target.

Building energy simulation programs compute numerical approximations to physical phenomena that can be modeled by a system of differential algebraic equations (DAE). For a large class of building energy analysis problems, one can prove that the DAE system has a unique once continuously differentiable solution. Consequently, if building simulation programs are built on models that satisfy the smoothness assumptions required to prove existence of a unique smooth solution, and if their numerical solvers allow controlling the approximation error, one can use such programs with Generalized Pattern Search optimization algorithms that adaptively control the precision of the solutions of the DAE system. Those optimization algorithms construct sequences of iterates with stationary accumulation points and have been shown to yield a significant reduction in computation time compared to algorithms that use fixed precision cost function evaluations. In this paper, we state the required smoothness assumptions and present the theorems that state existence of a unique smooth solution of the DAE system. We present BuildOpt, a detailed thermal and daylighting building energy simulation program. We discuss examples that explain the smoothing techniques used in BuildOpt. We present numerical experiments that compare the computation time for an annual simulation with the smoothing techniques applied to different parts of the models. The experiments show that high precision approximate solutions can only be computed if smooth models are used. This is significant because today's building simulation programs do not use such smoothing techniques and their solvers frequently fail to obtain a numerical solution if the solver tolerances are tight. We also present how BuildOpt's approximate solutions converge to a smooth function as the precision parameter of the numerical solver is tightened.

The heat transfer abilities of fluids can be improved by adding small particles of sizes of the order of nanometers. Recently a lot of research has been done in evaluating the thermal conductivity of nanofluids using various nanoparticles. In our present work we address this issue by conducting a series of experiments to determine the effective thermal conductivity of alumina-nanofluids by varying the base fluid with water and antifreeze liquids like ethylene glycol and propylene glycol. Temperature oscillation method is used to find the thermal conductivity of the nanofluid. The results show the thermal conductivity enhancement of nanofluids depends on viscosity of the base fluid. Finally the results are validated with a recently proposed theoretical model.

Building performance simulation tools have significantly improved in quality and depth of analysis capability over the past thirty-five years. Yet despite these increased capabilities, simulation programs still depend on user entry for significant data about building components, loads, and other typically scheduled inputs. This often forces users to estimate values or find previously compiled sets of data for these inputs. Often there is little information about how the data were derived, what purposes it is fit for, which standards apply, uncertainty associated with each data field as well as a general description of the data.

A similar problem bedeviled access to weather data and Crawley, Hand, and Lawrie (1999) described a generalized weather data format developed for use with two energy simulation programs which has subsequently lead to a repository which is accessed by thousands of practitioners each year.

This paper describes a generalized format and data documentation for user input—whether it is building envelope components, scheduled loads, or environmental emissions—the widgets upon which all models are dependant. We present several examples of the new input data format including building envelope component, a scheduled occupant load, and environmental emissions.

The growing interest in commissioning is creating a demand that will increasingly be met by mechanical contractors and less experienced commissioning agents. They will need tools to help them perform commissioning effectively and efficiently. The widespread availability of standardized procedures, accessible in the field, will allow commissioning to be specified with greater certainty as to what will be delivered, enhancing the acceptance and credibility of commissioning. In response, a functional test data analysis tool is being developed to analyze the data collected during functional tests for air-handling units.

The functional test data analysis tool is designed to analyze test data, assess performance of the unit under test and identify the likely causes of the failure. The tool has a convenient user interface to facilitate manual entry of measurements made during a test. A graphical display shows the measured performance versus the expected performance, highlighting significant differences that indicate the unit is not able to pass the test. The tool is described as semi-automated because the measured data need to be entered manually, instead of being passed from the building control system automatically. However, the data analysis and visualization are fully automated. The tool is designed to be used by commissioning providers conducting functional tests as part of either new building commissioning or retro-commissioning, as well as building owners and operators interested in conducting routine tests periodically to check the performance of their HVAC systems.

JF - 13th National Conference on Building Commissioning
T3 - Proceedings of the 13th National Conference on Building Commissioning
CY - New York City, NY
U2 - LBNL-58648
U4 -

A hybrid simulation environment for controls testing and training is described. A real-time simulation of a building and HVAC system is coupled to a real building control system using a hardware interface. A prototype has been constructed and tested in which the dynamic performance of both the HVAC equipment and the building envelope is simulated using SPARK (Simulation Problem Analysis and Research Kernel). A low cost hardware interface between the simulation and the real control system is implemented using plug-in analog-to-digital and digital-to-analog cards in a personal computer. The design and implementation of the hardware interface in SPARK are described. The development of a variant of this environment that uses a derivative of EnergyPlus to test the implementation of a natural ventilation control strategy in real control hardware is also described.

Various applications of the hybrid simulation environment are briefly described, including the development of control algorithms and strategies, control system product testing and the pre-commissioning of building control system installations. The application to the education and training of building operators and HVAC service technicians is discussed in more detail, including the development of a community college curriculum that includes the use of the hybrid simulation environment to teach both control system configuration and HVAC troubleshooting.

A nanofluid is a fluid containing suspended solid particles, with sizes on the order of nanometers. Normally, nanofluids have higher thermal conductivities than their base fluids. Therefore, it is of interest to predict the effective thermal conductivity of such a nanofluid under different conditions, especially since only limited experimental data are available. We have developed a technique to compute the effective thermal conductivity of a nanofluid using Brownian dynamics simulation, which has the advantage of being computationally less expensive than molecular dynamics, and have coupled that with the equilibrium Green-Kubo method. By comparing the results of our calculation with the available experimental data, we show that our technique predicts the thermal conductivity of nanofluids to a good level of accuracy.

Building energy simulation programs compute numerical approximations to physical phenomena that can be modeled by a system of differential algebraic equations (DAE). For a large class of building energy analysis problems, one can prove that the DAE system has unique solution that is once continuously differentiable in the building design parameters. Consequently, if building simulation programs are built on models that satisfy the smoothness assumptions required to prove existence of a unique smooth solution, and if their numerical solvers allow controlling the approximation error, one can use such programs with generalized pattern search optimization algorithms that adaptively control the precision of the solutions of the DAE system. Those optimization algorithms construct sequences of iterates with stationary accumulation points and have been shown to yield a significant reduction in computation time compared to algorithms that use fixed precision cost function evaluations. In this paper, we state the required smoothness assumptions and present the theorems that state existence of a unique smooth solution of the DAE system. We present BuildOpt, a detailed thermal and daylighting building energy simulation program. We discuss examples that explain the smoothing techniques used in BuildOpt. We present numerical experiments that compare the computation time for an annual simulation with the smoothing techniques applied to different parts of the models. The experiments show that high precision approximate solutions can only be computed if smooth models are used. This is significant because today's building simulation programs do not use such smoothing techniques and their solvers frequently fail to obtain a numerical solution if the solver tolerances are tight. We also present how BuildOpt's approximate solutions converge to a smooth function as the precision parameter of the numerical solver is tightened.

In solving optimization problems for building design and control, the cost function is often evaluated using a detailed building simulation program. These programs contain code features that cause the cost function to be discontinuous. Optimization algorithms that require smoothness can fail on such problems. Evaluating the cost function is often so time-consuming that stochastic optimization algorithms are run using only a few simulations, which decreases the probability of getting close to a minimum. To show how applicable direct search, stochastic, and gradient-based optimization algorithms are for solving such optimization problems, we compare the performance of these algorithms in minimizing cost functions with different smoothness. We also explain what causes the large discontinuities in the cost functions.

Thermal building simulation programs, such as EnergyPlus, compute numerical approximations to solutions of systems of differential algebraic equations. We show that the exact solutions of these systems are usually smooth in the building design parameters, but that the numerical approximations are usually discontinuous due to adaptive solvers and finite precision computations. If such approximate solutions are used in conjunction with optimization algorithms that depend on smoothness of the cost function, one needs to compute high precision solutions, which can be prohibitively expensive if used for all iterations. For such situations, we have developed an adaptive simulation–precision control algorithm that can be used in conjunction with a family of derivative free optimization algorithms. We present the main ingredients of the composite algorithms, we prove that the resulting composite algorithms construct sequences with stationary accumulation points, and we show by numerical experiments that using coarse approximations in the early iterations can significantly reduce computation time.

The design for the new Federal Building for San Francisco includes an office tower that is to be naturally ventilated. Each floor is designed to be cross-ventilated, through upper windows that are controlled by the building management system. Users have control over lower level windows, which can be as much as 50% of the total openable area. There are significant differences in the performance and the control of the windward and leeward sides of the building, and separate monitoring and control strategies are determined for each side. The performance and control of the building has been designed and tested using a modified version of EnergyPlus. Results from studies with EnergyPlus and computational fluid dynamics are used in designing the control strategy. Wind-driven cross-ventilation produces a main jet through the upper openings of the building, across the ceiling from the windward to the leeward side. Below this jet, the occupied regions are subject to a recirculating airflow. Results show that temperatures within the building are predicted to be satisfactory, provided a suitable control strategy is implemented that uses night cooling in periods of hot weather. The control strategy has 10 window opening modes. EnergyPlus was extended to simulate the effects of these modes, and to assess the effects of different forms of user behaviour. The results show how user behaviour can significantly influence the building performance.

The objective of this study was to demonstrate the potential for reducing peak-period electrical demand in moderate-weight commercial buildings by modifying the control of the HVAC system. An 80,000 ft2 office building with a medium-weight building structure and high window-to-wall ratio was used for a case study in which zone temperature set-points were adjusted prior to and during occupancy. HVAC performance data and zone temperatures were recorded using the building control system. Additional operative temperature sensors for selected zones and power meters for the chillers and the AHU fans were installed for the study. An energy performance baseline was constructed from data collected during normal operation. Two strategies for demand shifting using the building thermal mass were then programmed in the control system and implemented progressively over a period of one month. It was found that a simple demand limiting strategy performed well in this building. This strategy involved maintaining zone temperatures at the lower end of the comfort region during the occupied period up until 2 pm. Starting at 2 pm, the zone temperatures were allowed to float to the high end of the comfort region. With this strategy, the chiller power was reduced by 80-100% (1 - 2.3 W/ft2) during normal peak hours from 2 - 5 pm, without causing any thermal comfort complaints. The effects on the demand from 2 - 5 pm of the inclusion of pre-cooling prior to occupancy are unclear.

JF - 2004 ACEEE Summer Study on Energy Efficiency in Buildings
CY - Pacific Grove, CA
U2 - LBNL-55800
ER -
TY - Generic
T1 - Photovoltaic and Solar Thermal Modeling with the EnergyPlus Calculation Engine
T2 - World Renewable Energy Congress VIII and Expo
Y1 - 2004
A1 - Brent T. Griffith
A1 - Peter G. Ellis
JF - World Renewable Energy Congress VIII and Expo
CY - Denver, Colorado, USA
ER -
TY - Generic
T1 - Resources for Teaching Building Energy Simulation
T2 - SimBuild 2004, Building Sustainability and Performance Through Simulation
Y1 - 2004
A1 - Richard K. Strand
A1 - Richard J. Liesen
A1 - Michael J. Witte
JF - SimBuild 2004, Building Sustainability and Performance Through Simulation
CY - Boulder, Colorado, USA
ER -
TY - Generic
T1 - Simulation of Tubular Daylighting Devices and Daylighting Shelves in EnergyPlus
T2 - SimBuild 2004, Building Sustainability and Performance Through Simulation
Y1 - 2004
A1 - Peter G. Ellis
A1 - Richard K. Strand
A1 - Kurt T. Baumgartner
JF - SimBuild 2004, Building Sustainability and Performance Through Simulation
CY - Boulder, Colorado, USA
ER -
TY - THES
T1 - Simulation-Based Building Energy Optimization
T2 - Mechanical Engineering
Y1 - 2004
A1 - Michael Wetter
JF - Mechanical Engineering
PB - University of California, Berkeley
CY - Berkeley, CA, USA
VL - Ph.D.
ER -
TY - ABST
T1 - Simulation-based building energy optimization
Y1 - 2004
A1 - Michael Wetter
KW - dissertation
AB - This dissertation presents computational techniques for simulation-based design optimization of buildings and heating, ventilation, air-conditioning and lighting systems in which the cost function is smooth. In such problems, the evaluation of the cost function involves the numerical solution of systems of differential algebraic equations (DAE). Since the termination criteria of the iterative solvers often depend on the design parameters, a computer code for solving such systems usually denes a numerical approximation to the cost function that is discontinuous in the design parameters. The discontinuities can be large in cost functions that are evaluated by commercial building energy simulation programs, and optimization algorithms that require smoothness frequently fail if used with such programs. Furthermore, controlling the numerical approximation error is often not possible with commercial building energy simulation programs. In this dissertation, we present BuildOpt, a new detailed thermal building and daylighting simulation program. BuildOpt's simulation models dene a DAE system that is smooth in the state variables, in time and in the design parameters. This allows proving that the DAE system has a unique solution that is smooth in the design parameters, and it is required to compute high precision approximating cost functions that converge to a cost function that is smooth in the design parameters as the DAE solver tolerance is tightened. For simulation programs that allow such a precision control, we constructed subprocedures for Generalized Pattern Search (GPS) optimization algorithms that adaptively control the precision of the cost function evaluations: coarse precision for the early iterations,with precision progressively increasing as a stationary point is approached. This scheme signicantly reduces the computation time, and it allows to prove that the sequence of iterates contains stationary accumulation points. For optimization problems in which commercial building energy simulation programs are used to evaluate the cost function, we compared by numerical experiment several deterministic and probabilistic optimization algorithms.
ER -
TY - Generic
T1 - A simulation-based testing and training environment for building controls
T2 - Simbuild 2004
Y1 - 2004
A1 - Peng Xu
A1 - Philip Haves
A1 - Joseph J Deringer
AB - A hybrid simulation environment for controls testing and training is described. A real-time simulation of a building and HVAC system is coupled to a real building control system using a hardware interface. A prototype has been constructed and tested in which the dynamic performance of both the HVAC equipment and the building envelope is simulated using SPARK (Simulation Problem Analysis and Research Kernel). A low cost hardware interface between the simulation and the real control system is implemented using plug-in analog-to-digital and digital-to-analog cards in a personal computer. The design and implementation of the hardware interface in SPARK are described. The development of a variant of this environment that uses a derivative of EnergyPlus to test the implementation of a natural ventilation control strategy in real control hardware is also described. Various applications of the hybrid simulation environment are briefly described, including the development of control algorithms and strategies, control system product testing and the pre-commissioning of building control system installations. The application to the education and training of building operators and HVAC service technicians is discussed in more detail, including the development of a community college curriculum that includes the use of the hybrid simulation environment to teach both control system configuration and HVAC troubleshooting.
JF - Simbuild 2004
CY - Boulder, CO
U2 - LBNL-55801
ER -
TY - CONF
T1 - Specification and Implementation of IFC Based Performance Metrics to Support Building Life Cycle Assessment of Hybrid Energy Systems
T2 - SimBuild 2004: Building Sustainability and Performance Through Simulation
Y1 - 2004
A1 - Elmer Morrissey
A1 - James O'Donnell
A1 - Marcus Keane
A1 - Vladimir Bazjanac
JF - SimBuild 2004: Building Sustainability and Performance Through Simulation
CY - Boulder, CO
U1 -

A Virtual Building Environment (VBE) is a place where building industry project staffs can get help in creating Building Information Models (BIM) and in the use of virtual buildings. It consists of a group of industry software that is operated by industry experts who are also experts in the use of that software. The purpose of a VBE is to facilitate expert use of appropriate software applications in conjunction with each other to efficiently support multidisciplinary work. This paper defines BIM and virtual buildings, and describes VBE objectives, set-up and characteristics of operation. It informs about the VBE Initiative and the benefits from a couple of early VBE projects.

JF - European Conference on Product and Process Modeling in the Building and Construction Industry (ECPPM) 2004
CY - Istanbul, Turkey
U1 -

ER -
TY - Generic
T1 - Comparison of a generalized pattern search and a genetic algorithm optimization method
T2 - Proc. of the 8th IBPSA Conference
Y1 - 2003
A1 - Michael Wetter
A1 - Jonathan A. Wright
ED - Godfried Augenbroe
ED - Jan Hensen
AB - Building and HVAC system design can significantly improve if numerical optimization is used. However, if a cost function that is smooth in the design parameter is evaluated by a building energy simulation program, it usually becomes replaced with a numerical approximation that is discontinuous in the design parameter. Moreover, many building simulation programs do not allow obtaining an error bound for the numerical approximations to the cost function. Thus, if a cost function is evaluated by such a program, optimization algorithms that depend on smoothness of the cost function can fail far from a minimum. For such problems it is unclear how the Hooke-Jeeves Generalized Pattern Search optimization algorithm and the simple Genetic Algorithm perform. The Hooke-Jeeves algorithm depends on smoothness of the cost function, whereas the simple Genetic Algorithm may not even converge if the cost function is smooth. Therefore, we are interested in how these algorithms perform if used in conjunction with a cost function evaluated by a building energy simulation program. In this paper we show what can be expected from the two algorithms and compare their performance in minimizing the annual primary energy consumption of an office building in three locations. The problem has 13 design parameters and the cost function has large discontinuities. The optimization algorithms reduce the energy consumption by 7% to 32%, depending on the building location. Given the short labor time to set up the optimization problems, such reductions can yield considerable economic gains.
JF - Proc. of the 8th IBPSA Conference
CY - Eindhoven, Netherlands
VL - III
UR - http://www.ibpsa.org/proceedings/BS2003/BS03_1401_1408.pdf
ER -
TY - JOUR
T1 - Computer Measurement and Automation System for Gas-fired Heating Furnace
JF - Journal of Harbin Institute of Technology (Chinese)
Y1 - 2003
A1 - Xiufeng Pang
A1 - Yongcheng Jiang
A1 - Yan-shu Miao
A1 - Jun Xiong
VL - 35
IS - 3
ER -
TY - Generic
T1 - A convergent optimization method using pattern search algorithms with adaptive precision simulation
T2 - Proceedings of the 8th IBPSA Conference
Y1 - 2003
A1 - Michael Wetter
A1 - Elijah Polak
ED - Godfried Augenbroe
ED - Jan Hensen
KW - coordinate search
KW - direct search
KW - genetic algorithm
KW - hooke–jeeves
KW - optimization
KW - particle swarm optimization
AB -

In solving optimization problems for building design and control, the cost function is often evaluated using a detailed building simulation program. These programs contain code features that cause the cost function to be discontinuous. Optimization algorithms that require smoothness can fail on such problems. Evaluating the cost function is often so time-consuming that stochastic optimization algorithms are run using only a few simulations, which decreases the probability of getting close to a minimum. To show how applicable direct search, stochastic, and gradient-based optimization algorithms are for solving such optimization problems, we compare the performance of these algorithms in minimizing cost functions with different smoothness. We also explain what causes the large discontinuities in the cost functions.

Energy simulation (ES) and computational fluid dynamics (CFD) can play important roles in building design by providing complementary information about the buildings' environmental performance. However, separate applications of ES and CFD are usually unable to give an accurate prediction of building performance due to the assumptions involved in the separate calculations. Integration of ES and CFD eliminates many of these assumptions since the information provided by the models is complementary. Several different approaches to integrating ES and CFD are described. In order to bridge the discontinuities of time-scale, spatial resolution and computing speed between ES and CFD programs, a staged coupling strategy for different problems is proposed. The paper illustrates a typical dynamic coupling process by means of an example implemented using the EnergyPlus and MIT-CFD programs.

An appraisal of the potential performance of different Low Energy Cooling (LEC) systems in nonresidential buildings in California is being conducted using computer simulation. The paper presents results from the first phase of the study, which addressed the systems that can be modeled, with the DOE-2.1E simulation program.

The following LEC technologies were simulated as variants of a conventional variable-air-volume system with vapor compression cooling and mixing ventilation in the occupied spaces:

Air-side indirect and indirect/direct evaporative pre-cooling

Cool beams

Displacement ventilation

Results are presented for four populous climates, represented by Oakland, Sacramento, Pasadena and San Diego. The greatest energy savings are obtained from a combination of displacement ventilation and air-side indirect/direct evaporative pre-cooling. Cool beam systems have the lowest peak demand but do not reduce energy consumption significantly because the reduction in fan energy is offset by a reduction in air-side free cooling. Overall, the results indicate significant opportunities for LEC technologies to reduce energy consumption and demand in non-residential new construction and retrofit.

An automated fault detection and diagnosis tool for HVAC systems is being developed, based on an integrated, life-cycle, approach to commissioning and performance monitoring. The tool uses component-level HVAC equipment models implemented in the SPARK equation-based simulation environment. The models are configured using design information and component manufacturers' data and then fine-tuned to match the actual performance of the equipment by using data measured during functional tests of the sort using in commissioning. This paper presents the results of field tests of mixing box and VAV fan system models in an experimental facility and a commercial office building. The models were found to be capable of representing the performance of correctly operating mixing box and VAV fan systems and detecting several types of incorrect operation.

An automated fault detection and diagnosis tool for HVAC systems is being developed, based on an integrated, lifecycle, approach to commissioning and performance monitoring. The tool uses component-level HVAC equipment models implemented in the SPARK equation-based simulation environment. The models are configured using design information and component manufacturers' data and then fine-tuned to match the actual performance of the equipment by using data measured during functional tests of the sort using in commissioning. This paper presents the results of field tests of mixing box and VAV fan system models in an experimental facility and a commercial office building. The models were found to be capable of representing the performance of correctly operating mixing box and VAV fan systems and detecting several types of incorrect operation.

JF - 2002 ACEEE Summer Study on Energy Efficiency in Buildings
CY - Asilomar, California, USA
U2 - LBNL-50678
ER -
TY - Generic
T1 - HVAC Component Data Modeling Using Industry Foundation Classes
T2 - System Simulation in Buildings ’02
Y1 - 2002
A1 - Vladimir Bazjanac
A1 - James Forester
A1 - Philip Haves
A1 - Darko Sucic
A1 - Peng Xu
AB - The Industry Foundation Classes (IFC) object data model of buildings is being developed by the International Alliance for Interoperability (IAI). The aim is to support data sharing and exchange in the building and construction industry across the life-cycle of a building. This paper describes a number of aspects of a major extension of the HVAC part of the IFC data model. First is the introduction of a more generic approach for handling HVAC components. This includes type information, which corresponds to catalog data, occurrence information, which defines item-specific attributes such as location and connectivity, and performance history information, which documents the actual performance of the component instance over time. Other IFC model enhancements include an extension of the connectivity model used to specify how components forming a system can be traversed and the introduction of time-based data streams. This paper includes examples of models of particular types of HVAC components, such as boilers and actuators, with all attributes included in the definitions. The paper concludes by describing the on-going process of model testing, implementation and integration into the complete IFC model and how the model can be used by software developers to support interoperability between HVAC-oriented design and analysis tools.
JF - System Simulation in Buildings ’02
CY - Liège, Belgium
U2 - LBNL-51365
ER -
TY - Generic
T1 - The Integration of Engineering and Architecture: a Perspective on Natural Ventilation for the new San Francisco Federal Building
T2 - 2002 ACEEE Summer Study on Energy Efficiency in Buildings
Y1 - 2002
A1 - Erin McConahey
A1 - Philip Haves
A1 - Tim Chirst
AB -

A description of the in-progress design of a new Federal Office Building for San Francisco is used to illustrate a number of issues arising in the design of large, naturally ventilated office buildings. These issues include the need for an integrated approach to design involving the architects, mechanical and structural engineers, lighting designers and specialist simulation modelers. In particular, the use of natural ventilation, and the avoidance of air-conditioning, depends on the high degree of exposed thermal mass made possible by the structural scheme and by the minimization of solar heat gains while maintaining the good daylighting that results from optimization of the façade. Another issue was the need for a radical change in interior space planning in order to enhance the natural ventilation; all the individual enclosed offices are located along the central spine of each floorplate rather than at the perimeter. The role of integration in deterring the undermining of the design through value engineering is discussed. The comfort criteria for the building were established based on the recent extension to the ASHRAE comfort standard based on the adaptive model for naturally ventilated buildings. The building energy simulation program EnergyPlus was used to compare the performance of different natural ventilation strategies. The results indicate that, in the San Francisco climate, wind-driven ventilation provides sufficient nocturnal cooling to maintain comfortable conditions and that external chimneys do not provide significant additional ventilation at times when it when it would be beneficial.

This paper discusses a demonstration of a technology to address the problem that buildings do not perform as well as anticipated during design. We partnered with an innovative building operator to evaluate a prototype information monitoring and diagnostic system (IMDS). The IMDS consists of a set of high-quality sensors, data acquisition software and hardware, and data visualization software including a web-based remote access system, that can be used to identify control problems and equipment faults. The information system allowed the operators to make more effective use of the building control system and freeing up time to take care of other tenant needs. They report observing significant improvements in building comfort, potentially improving tenant health and productivity. The reduction in the labor costs to operate the building is about US$ 20,000 per year, which alone could pay for the information system in about 5 years. A control system retrofit based on findings from the information system is expected to reduce energy use by 20% over the next year, worth over US$ 30,000 per year in energy cost savings. The operators are recommending that similar technology be adopted in other buildings.

Selecting the model is an important and essential step in model based fault detection and diagnosis (FDD). Factors that are considered in evaluating a model include accuracy, training data requirements, calibration effort, generality, and computational requirements. The objective of this study was to evaluate different modeling approaches for their applicability to model based FDD of vapor compression chillers. Three different models were studied: the Gordon and Ng Universal Chiller model (2nd generation) and a modified version of the ASHRAE Primary Toolkit model, which are both based on first principles, and the DOE-2 chiller model, as implemented in CoolToolsTM, which is empirical. The models were compared in terms of their ability to reproduce the observed performance of an older, centrifugal chiller operating in a commercial office building and a newer centrifugal chiller in a laboratory. All three models displayed similar levels of accuracy. Of the first principles models, the Gordon-Ng model has the advantage of being linear in the parameters, which allows more robust parameter estimation methods to be used and facilitates estimation of the uncertainty in the parameter values. The ASHRAE Toolkit Model may have advantages when refrigerant temperature measurements are also available. The DOE-2 model can be expected to have advantages when very limited data are available to calibrate the model, as long as one of the previously identified models in the CoolTools library matches the performance of the chiller in question.

A great deal of research has examined the weather sensitivity of energy consumption in commercial buildings; however, the recent power crisis in California has given greater importance to peak demand. Several new loadshedding programs have been implemented or are under consideration. Historically, the target customers have been large industrial users who can reduce the equivalent load of several large office buildings. While the individual load reduction from an individual office building may be less significant, there is ample opportunity for load reduction in this area. The load reduction programs and incentives for industrial customers may not be suitable for commercial building owners. In particular, industrial customers are likely to have little variation in load from day to day. Thus a robust baseline accounting for weather variability is required to provide building owners with realistic targets that will encourage them to participate in load shedding programs.

The efficiencies of methods employed in solution of building simulation models are considered and compared by means of benchmark testing. Direct comparisons between the Simulation Problem Analysis and Research Kernel (SPARK) and the HVACSIM+ programs are presented, as are results for SPARK versus conventional and sparse matrix methods. An indirect comparison between SPARK and the IDA program is carried out by solving one of the benchmark test suite problems using the sparse methods employed in that program. The test suite consisted of two problems chosen to span the range of expected performance advantage. SPARK execution times versus problem size are compared to those obtained with conventional and sparse matrix implementations of these problems. Then, to see if the results of these limiting cases extend to actual problems in building simulation, a detailed control system for a heating, ventilating and air conditioning (HVAC) system is simulated with and without the use of SPARK cut set reduction. Execution times for the reduced and non-reduced SPARK models are compared with those for an HVACSIM+ model of the same system. Results show that the graph-theoretic techniques employed in SPARK offer significant speed advantages over the other methods for significantly reducible problems and that by using sparse methods in combination with graph-theoretic methods even problem portions with little reduction potential can be solved efficiently.

The potential offered by computer simulation is often not realized: Due to the interaction of system variables, simulation users rarely know how to choose input parameter settings that lead to optimal performance of a given system. Thus, a program called GenOpt® that automatically determines optimal parameter settings has been developed.

GenOpt is a generic optimization program. It minimizes an objective function with respect to multiple parameters. The objective function is evaluated by a simulation program that is iteratively called by GenOpt. In thermal building simulation — which is the main target of GenOpt — the simulation program usually has text-based I/O. The paper shows how GenOpt's simulation program interface allows the coupling of any simulation program with text based I/O by simply editing a configuration file, avoiding code modification of the simulation program. By using object-oriented programming, a high-level interface for adding minimization algorithms to GenOpt's library has been developed. We show how the algorithm interface separates the minimization algorithms and GenOpt's kernel, which allows implementing additional algorithms without being familiar with the kernel or having to recompile it. The algorithms can access utility classes that are commonly used for minimization, such as optimality check, line-search, etc.

GenOpt has successfully solved various optimization problems in thermal building simulation. We show an example of minimizing source energy consumption of an office building using EnergyPlus, and of minimizing auxiliary electric energy of a solar domestic hot water system using TRNSYS. For both examples, the time required to set up the optimization was less than one hour, and the energy savings are about 15%, together with better daylighting usage or lower investment costs, respectively.

A nodal model has been developed to represent room heat transfer in displacement ventilation and chilled ceiling systems. The model uses precalculated air flow rates to predict the air temperature distribution and the division of the cooling load between the ventilation air and the chilled ceiling. The air movements in the plumes and the rest of the room are represented separately using a network of ten air nodes. The values of the capacity rate parameters are calculated by solving the heat and mass balance equations for each node using measured temperatures as inputs. Correlations between parameter values for a range of cooling loads and supply air flow rates are presented.

The air flow in the office ventilation system known as displacement ventilation is dominated by a gravity current from the inlet and buoyant plumes above internal heat sources. Calculations of the flow and heat transfer in a typical office room have been made for this type of ventilation system used in conjunction with chilled ceiling panels. These calculations have been made in parallel with full size test chamber experiments. It has been found that with higher values of internal load (45 and 72 W m−2 of floor area) the flow becomes quasi-periodic in nature. Complex lateral oscillations are seen in the plumes above the heat sources which impinge on the ceiling and induce significant recirculating flows in the room. The frequency spectra of the transient calculations show good agreement with those of the experimental results. Comparison is also made between calculated mean room air speeds and temperature profiles and measured values.

Energy simulation (ES) and computational fluid dynamics (CFD) can play important roles in building design by providing complementary information about the buildings' environmental performance. However, separate applications of ES and CFD are usually unable to give an accurate prediction of building performance due to the assumptions involved in the separate calculations. Integration of ES and CFD eliminates many of these assumptions since the information provided by the models is complementary. Several different approaches to integrating ES and CFD are described. In order to bridge the discontinuities of time-scale, spatial resolution and computing speed between ES and CFD programs, a staged coupling strategy for different problems is proposed. The paper illustrates a typical dynamic coupling process by means of an example implemented using the EnergyPlus and MIT-CFD programs.

The application of model-based performance assessment at the whole building level is explored. The information requirements for a simulation to predict the actual performance of a particular real building, as opposed to estimating the impact of design options, are addressed with particular attention to common sources of input error and important deficiencies in most simulation models. The role of calibrated simulations is discussed. The communication requirements for passive monitoring and active testing are identified and the possibilities for using control system communications protocols to link on-line simulation and energy management and control systems are discussed. The potential of simulation programs to act as "plug-and-play" components on building control networks is discussed.

JF - Building Simulation ’01
CY - Rio de Janeiro
ER -
TY - Generic
T1 - Better IAQ Through Integrating Design Tools For The HVAC Industry
T2 - Healthy Buildings 2000
Y1 - 2000
A1 - Tuomas Laine
A1 - Risto Kosonen
A1 - Kim Hagström
A1 - Panu Mustakallio
A1 - De-Wei Yin
A1 - Philip Haves
A1 - Qingyan Chen
AB - There is currently no effective combination of interoperable design tools to cover all critical aspects of the HVAC design process. Existing design tools are separately available, but require expertise and operating time that is beyond the scope of a normal design project. For example, energy analysis and computational fluid dynamics (CFD) tools are not used in practical design, leading to poor indoor air quality and/or unnecessary energy consumption in buildings. A prototype integrated software tool for demonstration, process mapping and proofofconcept purposes was developed under a new international, Finland/USA jointly funded development project BildIT. Individual design tools were simplified and adapted to specific applications and also integrated so that they can be used in a timely and effective manner by the designer. The core of the prototype linked together an architectural CAD system, a 3D space model, a CFD program and a building energy simulation program and it utilises real product data from manufacturer's software. Also the complex building design, construction, maintenance and retrofit processes were mapped to get a template for the structure of the integrated design tool.
JF - Healthy Buildings 2000
CY - Espoo, Finland
U2 - LBNL-48456
ER -
TY - JOUR
T1 - Building simulation: an overview of development and information sources
JF - Building and Environment
Y1 - 2000
A1 - Tianzhen Hong
A1 - Siaw K. Chou
A1 - T.Y. Bong
KW - building simulation
AB -

We review the state-of-the-art on the development and application of computer-aided building simulation by addressing some crucial questions in the field. Although the answers are not intended to be comprehensive, they are sufficiently varied to provide an overview ranging from the historical and technical development to choosing a suitable simulation program and performing building simulation. Popular icons of major interested agencies and simulation tools and key information sources are highlighted. Future trends in the design and operation of energy-efficient ‘green' buildings are briefly described.

The paper commences by reviewing the variety of technical approaches to the problem of detecting and diagnosing faulty operation in order to improve the actual performance of buildings. The review covers manual and automated methods, active testing and passive monitoring, the different classes of models used in fault detection, and methods of diagnosis. The process of model-based fault detection is then illustrated by describing the use of relatively simple empirical models of chiller energy performance to monitor equipment degradation and control problems. The CoolTools™ chiller model identification package is used to fit the DOE-2 chiller model to on-site measurements from a building instrumented with high quality sensors. The need for simple algorithms to reject transient data, detect power surges and identify control problems is discussed, as is the use of energy balance checks to detect sensor problems. The accuracy with which the chiller model can be expected to predict performance is assessed from the goodness of fit obtained and the implications for fault detection sensitivity and sensor accuracy requirements are discussed. A case study is described in which the model was applied retroactively to high-quality data collected in a San Francisco office building as part of a related project (Piette et al. 1999).

A qualitative comparison is presented between three current North American and U.K. design cooling load calculation methods. The methods compared are the ASHRAE Heat Balance Method, the Radiant Time Series Method and the Admittance Method, used in the U.K. The methods are compared and contrasted in terms of their overall structure. In order to generate the values of the 24 hourly cooling loads, comparison was also made in terms of the processing of the input data and the solution of the equations required. Specific comparisons are made between the approximations used by the three calculation methods to model some of the principal heat transfer mechanisms. Conclusions are drawn regarding the ability of the simplified methods to correctly predict peak-cooling loads compared to the Heat Balance Method predictions. Comment is also made on the potential for developing similar approaches to cooling load calculation in the U.K. and North America in the future.

VL - 6
IS - 1
ER -
TY - Generic
T1 - Use of an Information Monitoring and Diagnostic System for Commissioning and Ongoing Operations
T2 - 8th National Conference on Building Commissioning PECI
Y1 - 2000
A1 - Mary Ann Piette
A1 - Satkartar T. Khalsa
A1 - Philip Haves
AB - This paper discusses a demonstration of a technology to address the problem that buildings do not perform as well as anticipated during design. We partnered with an innovative building operator to evaluate a prototype Information Monitoring and Diagnostic System (IMDS). The IMDS consists of a set of high-quality sensors, data acquisition software and hardware, and data visualization software, including a web-based remote access system that can be used to identify control problems and equipment faults. The IMDS allowed the operators to make more effective use of the control system, freeing up time to take care of other tenant needs. The operators report observing significant improvements in building comfort, potentially improving tenant health and productivity. Reduction in hours to operate the building are worth about $20,000 per year, which alone could pay for the IMDS in about five years. A control system retrofit based on findings from the IMDS is expected to reduce energy use by 20 percent over the next year, worth over $30,000 per year in energy cost savings. The operators recommend that similar technology be adopted in other buildings. While the current IMDS is oriented toward manual, human-based diagnostic techniques, we also evaluated automated diagnostic techniques. Strategies for utilizing results from this demonstration to influence commercial building performance monitoring for commissioning and operations will be discussed. Background
JF - 8th National Conference on Building Commissioning PECI
UR - http://imds.lbl.gov/pubs/paper383.pdf
ER -
TY - JOUR
T1 - A design day for building load and energy estimation
JF - Building and Environment
Y1 - 1999
A1 - Tianzhen Hong
A1 - Siaw K. Chou
A1 - T.Y. Bong
KW - building simulation
KW - design day
KW - doe-2
KW - peak load calculation
KW - weather data
AB -

We describe how a design day for building energy performance simulation can be selected from a typical meteorological year of a location. The advantages of the design day weather file are its simplicity and flexibility in use with simulation programs. The design day is selected using a weather parameter comprising the daily average dry bulb temperature and total solar insolation. The selection criterion addresses the balance between the need to minimise the part-load performance of the air-conditioning systems and plants and the number of hours of load not met. To validate the versatility of the design day weather file, we compare simulation results of the peak load and load profile of a building obtained from the DOE-2.1E code and a specially developed load estimation program, PEAKLOAD. PEAKLOAD is developed using the transfer function method and ASHRAE databases. Comparative results are in good agreement, indicating that a design day thus selected can be used when quick answers are required and simulations using a TMY file cannot be easily done or justified.

A nodal model has been developed to represent room heat transfer in displacement ventilation and chilled ceiling systems. The model uses precalculated air flow rates to predict the air temperature distribution and the division of the cooling load between the ventilation air and the chilled ceiling. The air movements in the plumes and the rest of the room are rep- resented separately using a network of ten air nodes. The values of the capacity rate parameters are calculated by solving the heat and mass balance equations for each node using measured temperatures as inputs. Correlations between parameter values for a range of cooling loads and supply air flow rates are presented.

JF - Building Simulation ’99
CY - Kyoto, Japan
UR - http://www.ibpsa.org/proceedings/BS1999/BS99_D-05.pdf
ER -
TY - Generic
T1 - Numerical Performance of a Graph-Theoretic HVAC Simulation Program
T2 - Building Simulation ’99
Y1 - 1999
A1 - Edward F. Sowell
A1 - Philip Haves
AB - The Simulation Problem Analysis and Research Kernel (SPARK) uses graph-theoretic techniques to match equations to variables and build computational graphs, yielding solution sequences indicated by needed data flow. Additionally, the problem graph is decomposed into strongly connected components, thus reducing the size of simultaneous equation sets, and small cut sets are determined, thereby reducing the number of iteration variables needed to solve each equation set. The improvement in computational efficiency produced by this graph theoretic preprocessing depends on the nature of the problem. The paper explores the improvement one might expect in practice in three ways. First, two problems chosen to span the range of performance are studied and some of the factors determining the performance are identified and discussed. The problem selected to exhibit a large improvement consists of a set of sparsely coupled non-linear equations. The problem selected to represent the other end of the performance spectrum is a set of equations obtained by discretizing Laplace's equation in two dimensions, e.g. a heat conduction problem. Execution time versus problem size is compared to that obtained with sparse matrix implementations of the same problems. Then, to see if the results of these somewhat contrived limiting cases extend to actual problems in building simulation, a detailed control system model of a six- zone VAV HVAC system is simulated with and without the use of cut set reduction. Execution times are compared between the reduced and non-reduced SPARK models, and with those from an HVACSIM+ model of the same system.
JF - Building Simulation ’99
CY - Kyoto, Japan
UR - http://www.ibpsa.org/proceedings/BS1999/BS99_A-05.pdf
ER -
TY - Generic
T1 - The application of Problem Reduction Techniques Based on Graph Theory to the Simulation of Non-Linear Continuous Systems
T2 - EUROSIM’98
Y1 - 1998
A1 - Philip Haves
A1 - Edward F. Sowell
JF - EUROSIM’98
CY - Manchester, UK
ER -
TY - JOUR
T1 - Comparison of North American and U.K. Cooling Load Calculation Procedures - Methodology
JF - ASHRAE Transactions
Y1 - 1998
A1 - Jeffrey D. Spitler
A1 - Simon J. Rees
A1 - Philip Haves
AB - This paper describes the methodology used in a quanti- tative comparison between the current North American and United Kingdom cooling load calculation methods. Three calculation methods have been tested as part of a joint ASHRAE/CIBSE research project: the ASHRAE heat balance method and radiant time series method and the admittance method, used in the U.K. A companion paper (Rees et al.1998) describes the results of the study. The quantitative comparison is primarily organized as a parametric study—each building zone/weather day combination compared may be thought of as a combination of various parameters, e.g., exterior wall type, roof type, glazing area, etc. Specifically, this paper describes the overall organization of the study, the parameters and parameter levels that can be varied, and the tools developed to create input files, automate the load calculations, and extract the results. A brief descrip- tion of the cooling load calculation procedure implementa- tions is also given. The methodology presented and the tools described could also be used to make comparisons between other calculation methods.
VL - 104
IS - 2
ER -
TY - JOUR
T1 - Comparison of North American and U.K. Cooling Load Calculation Procedures - Results
JF - ASHRAE Transactions
Y1 - 1998
A1 - Simon J. Rees
A1 - Jeffrey D. Spitler
A1 - Philip Haves
AB - Calculation of design cooling loads is of critical concern to designers of HVAC systems. The work reported here has been carried out under a joint ASHRAE/CIBSE research project to compare design cooling calculation methods. Three calculation methods have been tested, the ASHRAE heat balance method and radiant time series method, and the admit- tance method, used in the U.K. The results presented in this paper show the general trends in over/underprediction of peak load in the simplified methods compared to the heat balance method. The performance of the simplified methods is explained in terms of some of the underlying assumptions in the methods and by reference to specific examples.
VL - 104
IS - 2
ER -
TY - Generic
T1 - Component-Based and Equation-Based Solvers for HVAC Simulation: a Comparison of HVACSIM+ and SPARK
T2 - System Simulation in Buildings '98
Y1 - 1998
A1 - Philip Haves
A1 - Edward F. Sowell
JF - System Simulation in Buildings '98
CY - Liège, Belgium
ER -
TY - JOUR
T1 - Outdoor synthetic temperature for the calculation of space heating load
JF - Energy and Buildings
Y1 - 1998
A1 - Tianzhen Hong
A1 - Yi Jiang
KW - heating load calculation
KW - outdoor design conditions
KW - residential buildings
KW - stochastic analysis
KW - thermal performance of buildings
AB -

Methods to select the outdoor design temperature (ODT) for heating load calculation specified in current design codes in different countries are firstly discussed. Then a new method namely Stochastic Analysis is presented to determine the outdoor synthetic temperature (OST), which fully considers the randomness of weather and internal casual gains, and the thermal performance of buildings. The concept of OST enables the design of space heating system to be the trade-off between economics and risk. Finally, case studies of the influence of different building components on OST of a residential room in Beijing have been studied, which shows that OST depends upon building structures as well as weather conditions. It is recommended that OST rather than ODT should be employed in heating load calculation hence, sizing equipment for space heating systems.

This paper, which reports the results of ASHRAE Research Project 825, describes the development of a set of tools and supporting data to facilitate the evaluation of HVAC control algorithms and strategies using computer simulation. The tools consist of a documented set of component models for use in two component-based HVAC simulation programs. New models have been developed to enable explicit simulation of flow rates and pressure drops in ventilation systems, particularly variable-air-volume (VAV) systems, and detailed simulation of algorithms and strategies used in HVAC control systems. A mixed-use building equipped with a VAV HVAC system has been extensively documented, and a detailed model of the fabric, mechanical equipment, and controls has been produced in order to illustrate the capabilities and use of the tools. Values for the parameters in the component models describing the fabric and mechanical equipment are based on construction drawings, manufacturer's specifications, surveys, and measurements. Detailed models of the strategies for fan control, supply air temperature control, and room temperature control were developed from the controls manufacturer's technical information and the configuration of the actual control system. A simulation model of the whole building was then assembled from the models of the fabric, mechanical equipment, and controls. Results obtained by exercising the test bed in order to demonstrate its use in evaluating the performance of interacting control loops are presented. The paper concludes by discussing possible applications and extensions of the test bed.

An integrated building simulation environment, IISABRE, is introduced. IISABRE consists of CABD, BTP and IISPAM. CABD is an AutoCAD-based building descriptor enabling users to draw a building and define information. Some design tools are built into CABD, and a STEP-based building database can be generated, which provides an open mechanism to share the building database with other programs. BTP is a program for the detailed dynamic simulation of building thermal performance. With a PC 486DX50 (8M RAM) running in MS-Windows 3.11, BTP needs about 40 minutes to calculate the annual hourly energy demand for a building with 20 zones. IISPAM is a knowledge-based system for translating the STEP-based building database into ASCII-based data files for BTP. IISABRE can be widely employed in the field of building environmental engineering in order to improve the energy efficiency of buildings and the thermal comfort of the indoor environment.

A new multizone model which is an improvement on the state space model is presented, which is potentially more efficient in the simulation of large scale buildings than other methods such as finite difference, transfer functions, or finite volume. The modeling philosophy is firstly discussed. Then the principle and algorithm of the new model are described. Finally, a PC based program BTP developed based on state-of-the-art modeling strategy reveals its applicability with fast calculation speed and satisfactory accuracy in the modeling of building energy performance.

Describes a set of automated tests for use in commissioning the controls associated with coils and mixing boxes in air-handling units. The test procedures were developed using a computer simulation of an office building air conditioning system and were verified by manual testing in real buildings. A prototype automated commissioning system was then evaluated in blind tests on a large air conditioning test rig. Concludes that automated commissioning has the potential to reduce the cost and increase the thoroughness of HVAC controls commissioning. A prototype commissioning tool is under development based on the described approach.

The weather is a multi-dimensional stochastic process; the traditional typical or standard meteorological year is not enough to describe the random behaviour of weather. The model presented in this paper is based on the vector auto-regressive (VAR) time series method. From the validation results, it can be seen that the stochastic weather model is essential to describe real climate behaviour, and the accuracy obtained is sufficient for the application of the stochastic weather model in the simulation and stochastic analysis of building HVAC systems.

A methodology is presented for investigating the uncertainty properties of the building thermal processes caused by the random behaviour of the meteorological processes and the casual gains. A detailed building thermal model is used with a stochastic weather model and a random casual gain model. The probability distribution of the zone temperature of the building is calculated directly from these models. The overheating risk has been analysed as an example. The probability distribution of the periods when the zone temperature is higher than the demand temperature is calculated. The result shows all the possible situations rather than only a sample as would be obtained by running a normal simulation using given weather data. The influence of different building components on the overheating risk has been studied. The result shows that the most likely component for overheating risk in a residential building in Beijing is the window size. The thermal mass of the internal walls and the placing of windows have little effect on overheating risk.

Three complementary approaches may be used in the evaluation of the performance of building control systems-simulation, emulation and field testing. In emulation a real-time simulation of the building and HVAC plant is connected to a real building energy management system (BEMS) via a hardware interface. Emulation has the advantage of allowing controlled, repeatable experiments whilst testing real devices that may contain proprietary algorithms. Building emulators have been developed by the authors in the context of lEA Annex 17, which is concerned with the use of simulation to evaluate the performance of BEMS. The paper discusses different approaches to the design of building emulators and describes the different architectures, hardware and software used by the authors. The problem of evaluating the overall performance of BEMS is discussed and results are presented that illustrate the use of emulators to investigate the influence of the tuning of local loop controls on building performance.

Heating, cooling and lighting energy consumptions in buildings are inter-related, and a model which treats thermal performance and lighting simultaneously is required in order to evaluate the full benefits of daylighting in buildings. A lighting facility has been included in a dynamic building simulation program (SERI-RES) used in the Department of Energy's passive solar programme. Interior daylight illuminance is calculated using an extension of the daylight factor method. The lighting usage of various lighting systems is predicted from the daylight illuminance, and the thermal consequences of that lighting use included in the thermal simulation of the building. The applicability of the method described in this paper is not limited to SERI-RES. The method could be incorporated in any building energy analysis program intended for the UK or similar climates.

Fan and chiller energy savings achievable in commercial buildings with adjustable-speed drives are described. The savings are estimated with the aid of parametric simulations from a sophisticated, hourly building energy simulation model. Two prototypes-a single-zone retail store and a multizone medium office building-are simulated for five U.S. locations. The model incorporates part-load performance curves for both inlet vane and adjustable-speed drive controls for fans and centrifugal chillers. The results identify economic conditions that justify the added expense of adjustable-speed drives.

To better quantify the effects of conservation measures, degree.day-based techniques are commonly used to isolate weather.induced changes in building energy use. In this paper, we use a building energy simulation model, which allows us to hold fixed all influences on energy use besides weather, to evaluate several degree-day-based techniques. The evaluation is applied to simulated electricity and natural gas consumption for two large office building prototypes located in five U.8. climates. We review the development of degree day- based, weather-normalization techniques to identify issues for applying the techniques to office buildings and then evaluate the accuracy of the techniques with the simulated data. We conclude that, for the two office building prototypes and five U.8. locations examined, most techniques perform reasonably well; accuracy, in predicting annual consumption, is generally better than 10%. Our major finding is that accuracy among individual techniques is overwhelmed by circumstances outside the control of the analyst, namely, the choice of the initial year from which the normalization estimates are made.

Compilations of measured energy savings have shown that engineering calculations do not always correlate well with actual performance. One important difference between engineering calculations and real world performance is the effect of weather. Energy service companies, whose profits are a function of energy savings, and building energy researchers have developed weather-normalization formulas or techniques. True tests to determine the adequacy of these methods, however, require careful control of other determinants of building energy use. This paper describes results obtained by using a building energy simulation tool to evaluate some of these methods for commercial buildings. Degree-day-based normalization techniques designed to account for the effects of weather on commercial building energy use are identified. The normalization techniques are compared using the results of DOE-2 simulations for two office building prototypes using many years of actual weather data for a single location. We conclude that, for the prototypes and location examined, the techniques performed reasonably well, and the sophisticated techniques did not perform noticeably better than the simpler ones.

The thermal advantages of a roofpond as an element of a residential cooling system are described. The authors conducted heat transfer experiments at two roofpond residences (RPRs) at Trinity University; the authors used data from these experiments to validate RPR simulations. Results of measurements of vertical and horizontal temperature differences within roofponds are discussed. Horizontal heat transfer within one water bag was effective. Thermal resistance at the outer surface of a water bag with a deflated glazing can be significant. Simulation shows that an RPR can provide comfort without supplemental sensible cooling during almost all hours of a typical summer in any U.S climate. Ceiling fans are important in most climates. In the most demanding climates, the residence and the pond insulating panels must have high R-value. A map is included that provides RPR design guidance. The simulations indicate that dehumidification will be required to control mold, mildew, and ceiling condensation in an RPR in most climates; energy and power displacement by an RPR is sensitive to the humidity control required and the efficiency of the dehumidifier used.

This paper describes a study of the cooling energy requirements that result from thermal storage in building mass, and suggests methods for predicting and controlling its energy cost implications. The study relies on computer simulations of energy use for a large office building prototype in El Paso, TX using the DOE-2 building energy analysis program. Increased Monday cooling energy requirements resulting from the weekend shut-down of HVAC systems are documented. Predictors of energy use and peak demands, which account for thermal storage in building mass, are described. Load-shifting, sub-cooling and pre-cooling equipment operating strategies are evaluated with explicit reference to utility rate schedules.

Detailed heat flux and temperature measurements have been made in two residential scale roof pond buildings in San Antonio, Texas from July to November 1981. The minimum temprature of the 4 in deep roof pond sealed in PVC bags was approximately equal to the minimum ambient dry bulb temperature. The sensitivity of this equality to changes in meteorological conditions, maximum pond temperature and thermal load is evaluated using the measurements. Verified simulations are then used to evaluate the sensitivity of this equality to changes in the thermal load, and to changes in the depth, surface emittance and surface thermal resistance of the sealed pond in various climates. For the range of roof pond design options of interest in passive cooling of buildings, the minimum pond temperature was found to be within 2 F of the minimum ambient temperature in all climates considered. The equality of these minimum temperatures is advocated as a useful rule of thumb for feasibility assessment and as part of a simplified design methodology. The simulated minimum pond temperature was found to be surprisingly insensitive to a 50% decrease in the fraction of pond area exposed to the sky.

A number of advantages are claimed for earth sheltered buildings; the earth provides both insulation and thermal storage and also serves to reduce infiltration and noise. This paper seeks to quantify the thermal advantages of both earth sheltering and perimeter insulation by comparing the simulated thermal performance of an earth sheltered house, a house with perimeter insulation and a house with neither. The fuel savings are then compared to the estimated construction costs to determine cost-effectiveness. The major saving from an earth sheltered building is obtained in colder climates where the effective elevation of the frost line due to the earth berms considerably reduces the cost of the foundation.

Recent data on the polarization of extragalactic radio sources are used to investigate the distribution of Delta, the angle between the major axis of a source and the intrinsic position angle of the E vector of linear polarization. Previous work on this subject has led to widely divergent conclusions. It is found that sources of high radio luminosity usually have Delta near 90 deg, implying that the magnetic fields in such sources are oriented along the major axis. For radio galaxies with low luminosity, on the other hand, Delta tends to lie nearer zero deg.

Measurements of the linear polarization of extragalactic radio sources have been made over a range of wavelengths in order to study both the properties of the sources themselves and the Faraday rotation along the line of sight to the observer. As part of a continuing program of such measurements the flux densities and integrated polarizations of 226 sources (including 134 quasars) were observed at 966 MHz (lambda 31 cm), to complement previous measurements at lambda 49 and lambda 74 cm (Conway et al. 1972). These results have been combined with others at shorter wavelengths in a discussion of the polarization properties of quasars (Conway et al. 1974). All the sources have angular sizes of 1 arcmin or less

Observations over a wide range of wavelengths, 2.2 ≤ λ ≤ 73 cm, have been combined to define the wavelength variation of the degree of linear polarization m(λ) for 120 quasars with known redshift. For the majority, m(λ) decreases monotonically with increasing wavelength but for 35 sources the polarization curve is inverted at short wavelengths. A classification is given, based on both the polarization curve and the radio spectrum, and the results are interpreted in terms of the presence or absence of opaque components in the source. The depolarization which occurs at long wavelengths is accounted for by a combination of spectral effects and Faraday depolarization. For 46 steep-spectrum sources the depolarization curve appears to be dominated by the Faraday effect, and has been used to deduce the electron density within the radiating components. In this group of sources the correlation between depolarization and redshift noted by Kronberg et al. is confirmed and strengthened. A discussion is given of some theoretical models of radio sources in the light of the depolarization data.